Mass spectrometry-based targeted quantitative proteomics: achieving sensitive and reproducible detection of proteins

Proteomics quality and standard: from a regulatory perspective

Proteomics has emerged as a rapidly expanding field dealing with large-scale protein analyses. It is anticipated that proteomics data will be increasingly submitted to the U.S. Food and Drug Administration (FDA) for biomarker qualification or in conjunction with applications for the approval of drugs, medical devices, and other FDA-regulated consumer products. To date, however, no established guideline has been available regarding the generation, submission and assessment of the quality of proteomics data that will be reviewed by regulatory agencies for decision making. Therefore, this commentary is aimed at provoking some thoughts and debates towards developing a framework which can guide future proteomics data submission. The ultimate goal is to establish quality control standards for proteomics data generation and evaluation, and to prepare government agencies such as the FDA to meet future obligations utilizing proteomics data to support regulatory decision.

Cancer metabolism and mass spectrometry-based proteomics

Cancer metabolism has been extensively investigated by various tools, and the fact of diverse metabolic reprogramming in cancer cells has been gradually unveiled. In this review, we discuss some contributions in cancer metabolism by general proteomic analysis and post-translational modification analysis using mass spectrometry (MS) technique. Instead of following one or several metabolic enzymes/pathways, the current MS approach can quickly identify a large number of proteins and compare their expression levels in different samples, providing a potentially comprehensive picture of cancer metabolism. The MS analyses from pancreatic cancer cells support a hypothesis that hypoxia promotes cells in solid tumor to reprogram metabolic pathways in order to minimize the oxygen consumption. The oxidative stress in pancreatic cancer cells is lower than that in normal duct cells, and the cancer cells adaptively express less antioxidant proteins, contrary to claims that oxidative stress is higher in cancer cells. Separately, the MS analyses confirm that pyruvate kinase isoform 2 (PKM2) can be detected in both cancer and normal cells, disagreeing with report that tumor cells express exclusively PKM2. In addition, MS analyses from pancreatic cancer cells demonstrate that lactate dehydrogenase-B is significantly upregulated in pancreatic cancer cells, whereas previous reports show that lactate dehydrogenase-A is overexpressed and is responsible for lactate production in cancer cells. Lastly, the result from MS analysis suggests that the glutaminolysis in pancreatic cancer cells is different from that observed in glioblastoma cells.

Unlocking the puzzling biology of the black Périgord truffle Tuber melanosporum

The black Périgord truffle (Tuber melanosporum Vittad.) is a highly prized food today, with its unique scent (i.e., perfume) and texture. Despite these attributes, it remains relatively poorly studied, lacking "omics" information to characterize its biology and biochemistry, especially changes associated with freshness and the proteins/metabolites responsible for its organoleptic properties. In this study, we have functionally annotated the truffle proteome from the 2010 T. melanosporum genome comprising 12,771 putative nonredundant proteins. Using sequential BLAST search strategies, we identified homologues for 2587 proteins with 2486 (96.0%) fungal homologues (available from http://biolinfo.org/protannotator/blacktruffle.php). A combined 1D PAGE and high-accuracy LC-MS/MS proteomic study was employed to validate the results of the functional annotation and identified 836 (6.5%) proteins, of which 47.5% (i.e., 397) were present in our bioinformatics studies. Our study, functionally annotating 6487 black Périgord truffle proteins and confirming 836 by proteomic experiments, is by far the most comprehensive study to date contributing significantly to the scientific community. This study has resulted in the functional characterization of novel proteins to increase our biological understanding of this organism and to uncover potential biomarkers of authenticity, freshness, and perfume maturation.

Quantitative molecular phenotyping of gill remodeling in a cichlid fish responding to salinity stress

A two-tiered label-free quantitative (LFQ) proteomics workflow was used to elucidate how salinity affects the molecular phenotype, i.e. proteome, of gills from a cichlid fish, the euryhaline tilapia (Oreochromis mossambicus). The workflow consists of initial global profiling of relative tryptic peptide abundances in treated versus control samples followed by targeted identification (by MS/MS) and quantitation (by chromatographic peak area integration) of validated peptides for each protein of interest. Fresh water acclimated tilapia were independently exposed in separate experiments to acute short-term (34 ppt) and gradual long-term (70 ppt, 90 ppt) salinity stress followed by molecular phenotyping of the gill proteome. The severity of salinity stress can be deduced with high technical reproducibility from the initial global label-free quantitative profiling step alone at both peptide and protein levels. However, an accurate regulation ratio can only be determined by targeted label-free quantitative profiling because not all peptides used for protein identification are also valid for quantitation. Of the three salinity challenges, gradual acclimation to 90 ppt has the most pronounced effect on gill molecular phenotype. Known salinity effects on tilapia gills, including an increase in the size and number of mitochondria-rich ionocytes, activities of specific ion transporters, and induction of specific molecular chaperones are reflected in the regulation of abundances of the corresponding proteins. Moreover, specific protein isoforms that are responsive to environmental salinity change are resolved and it is revealed that salinity effects on the mitochondrial proteome are nonuniform. Furthermore, protein NDRG1 has been identified as a novel key component of molecular phenotype restructuring during salinity-induced gill remodeling. In conclusion, besides confirming known effects of salinity on gills of euryhaline fish, molecular phenotyping reveals novel insight into proteome changes that underlie the remodeling of tilapia gill epithelium in response to environmental salinity change.

Metabolo-proteomics to discover plant biotic stress resistance genes

Plants continuously encounter various environmental stresses and use qualitative and quantitative measures to resist pathogen attack. Qualitative stress responses, based on monogenic inheritance, have been elucidated and successfully used in plant improvement. By contrast, quantitative stress responses remain largely unexplored in plant breeding, due to complex polygenic inheritance, although hundreds of quantitative trait loci for resistance have been identified. Recent advances in metabolomic and proteomic technologies now offer opportunities to overcome the hurdle of polygenic inheritance and identify candidate genes for use in plant breeding, thus improving the global food security. In this review, we describe a conceptual background to the plant-pathogen relationship and propose ten heuristic steps streamlining the application of metabolo-proteomics to improve plant resistance to biotic stress.

Altered protein networks and cellular pathways in severe west nile disease in mice

Background

The recent West Nile virus (WNV) outbreaks in developed countries, including Europe and the United States, have been associated with significantly higher neuropathology incidence and mortality rate than previously documented. The changing epidemiology, the constant risk of (re-)emergence of more virulent WNV strains, and the lack of effective human antiviral therapy or vaccines makes understanding the pathogenesis of severe disease a priority. Thus, to gain insight into the pathophysiological processes in severe WNV infection, a kinetic analysis of protein expression profiles in the brain of WNV-infected mice was conducted using samples prior to and after the onset of clinical symptoms.

Methodology/Principal Findings

To this end, 2D-DIGE and gel-free iTRAQ labeling approaches were combined, followed by protein identification by mass spectrometry. Using these quantitative proteomic approaches, a set of 148 proteins with modified abundance was identified. The bioinformatics analysis (Ingenuity Pathway Analysis) of each protein dataset originating from the different time-point comparisons revealed that four major functions were altered during the course of WNV-infection in mouse brain tissue: i) modification of cytoskeleton maintenance associated with virus circulation; ii) deregulation of the protein ubiquitination pathway; iii) modulation of the inflammatory response; and iv) alteration of neurological development and neuronal cell death. The differential regulation of selected host protein candidates as being representative of these biological processes were validated by western blotting using an original fluorescence-based method.

Conclusion/Significance

This study provides novel insights into the in vivo kinetic host reactions against WNV infection and the pathophysiologic processes involved, according to clinical symptoms. This work offers useful clues for anti-viral research and further evaluation of early biomarkers for the diagnosis and prevention of severe neurological disease caused by WNV.

Ovarian cancer: can proteomics give new insights for therapy and diagnosis?

The study of the ovarian proteomic profile represents a new frontier in ovarian cancer research, since this approach is able to enlighten the wide variety of post-translational events (such as glycosylation and phosphorylation). Due to the possibility of analyzing thousands of proteins, which could be simultaneously altered, comparative proteomics represent a promising model of possible biomarker discovery for ovarian cancer detection and monitoring. Moreover, defining signaling pathways in ovarian cancer cells through proteomic analysis offers the opportunity to design novel drugs and to optimize the use of molecularly targeted agents against crucial and biologically active pathways. Proteomic techniques provide more information about different histological types of ovarian cancer, cell growth and progression, genes related to tumor microenvironment and specific molecular targets predictive of response to chemotherapy than sequencing or microarrays. Estimates of specificity with proteomics are less consistent, but suggest a new role for combinations of biomarkers in early ovarian cancer diagnosis, such as the OVA1 test. Finally, the definition of the proteomic profiles in ovarian cancer would be accurate and effective in identifying which pathways are differentially altered, defining the most effective therapeutic regimen and eventually improving health outcomes.

Clinical review: improving the measurement of serum thyroglobulin with mass spectrometry

CONTEXT

Serum thyroglobulin (Tg) measurements are central to the management of patients treated for differentiated thyroid carcinoma. For decades, Tg measurements have relied on methods that are subject to interference by commonly found substances in human serum and plasma, such as Tg autoantibodies. As a result, many patients need additional imaging studies to rule out cancer persistence or recurrence that could be avoided with more sensitive and specific testing methods.

OBJECTIVES

The aims of this review are to: 1) briefly review the interferences common to Tg immunoassays; 2) introduce readers to liquid chromatography-tandem mass spectrometry as a method for quantifying proteins in human serum/plasma; and 3) discuss the potential benefits and limitations of the method in the quantification of serum Tg.

RESULTS

Mass spectrometric methods have traditionally lacked the sensitivity, robustness, and throughput to be useful clinical assays. These methods failed to meet the necessary clinical benchmarks due to the nature of the mass spectrometry workflow and instrumentation. Over the past few years, there have been major advances in reagents, automation, and instrumentation for the quantification of proteins using mass spectrometry. More recently, methods using mass spectrometry to detect and quantify Tg have been developed and are of sufficient quality to be used in the management of patients.

CONCLUSIONS

Novel serum Tg assays that use mass spectrometry may avoid the issue of autoantibody interference and other problems with currently available immunoassays for Tg. Prospective studies are needed to fully understand the potential benefits of novel Tg assays to patients and care providers.

Mass spectrometry-based proteomics in molecular diagnostics: discovery of cancer biomarkers using tissue culture

Accurate diagnosis and proper monitoring of cancer patients remain a key obstacle for successful cancer treatment and prevention. Therein comes the need for biomarker discovery, which is crucial to the current oncological and other clinical practices having the potential to impact the diagnosis and prognosis. In fact, most of the biomarkers have been discovered utilizing the proteomics-based approaches. Although high-throughput mass spectrometry-based proteomic approaches like SILAC, 2D-DIGE, and iTRAQ are filling up the pitfalls of the conventional techniques, still serum proteomics importunately poses hurdle in overcoming a wide range of protein concentrations, and also the availability of patient tissue samples is a limitation for the biomarker discovery. Thus, researchers have looked for alternatives, and profiling of candidate biomarkers through tissue culture of tumor cell lines comes up as a promising option. It is a rich source of tumor cell-derived proteins, thereby, representing a wide array of potential biomarkers. Interestingly, most of the clinical biomarkers in use today (CA 125, CA 15.3, CA 19.9, and PSA) were discovered through tissue culture-based system and tissue extracts. This paper tries to emphasize the tissue culture-based discovery of candidate biomarkers through various mass spectrometry-based proteomic approaches.

Technical note: proteomic approaches to fundamental questions about neutrophil biology

Proteomics is one of a group of technologies that generates high-throughput, large-scale datasets that can be used to understand cell or organ functions at a systems level. This review will focus on the application of proteomics to the understanding of neutrophil biology. The strengths and weaknesses of common proteomic methods and their application to neutrophils are reviewed, with the goal of evaluating whether the technology is ready to advance our understanding of neutrophil biology.

Selected reaction monitoring to differentiate and relatively quantitate isomers of sulfated and unsulfated core 1 O-glycans from salivary MUC7 protein in rheumatoid arthritis

Rheumatoid arthritis is a common and debilitating systemic inflammatory condition affecting up to 1% of the world's population. This study aimed to investigate the immunological significance of O-glycans in chronic arthritis at a local and systemic level. O-Glycans released from synovial glycoproteins during acute and chronic arthritic conditions were compared and immune-reactive glycans identified. The sulfated core 1 O-glycan (Galβ1-3GalNAcol) was immune reactive, showing a different isomeric profile in the two conditions. From acute reactive arthritis, three isomers could be sequenced, but in patients with chronic rheumatoid arthritis, only a single 3-Gal sulfate-linked isomer could be identified. The systemic significance of this glycan epitope was investigated using the salivary mucin MUC7 in patients with rheumatoid arthritis and normal controls. To analyze this low abundance glycan, a selected reaction monitoring (SRM) method was developed to differentiate and relatively quantitate the core 1 O-glycan and the sulfated core 1 O-glycan Gal- and GalNAc-linked isomers. The acquisition of highly sensitive full scan linear ion trap MS/MS spectra in addition to quantitative SRM data allowed the 3- and 6-linked Gal isomers to be differentiated. The method was used to relatively quantitate the core 1 glycans from MUC7 to identify any systemic changes in this carbohydrate epitope. A statistically significant increase in sulfation was identified in salivary MUC7 from rheumatoid arthritis patients. This suggests a potential role for this epitope in chronic inflammation. This study was able to develop an SRM approach to specifically identify and relatively quantitate sulfated core 1 isomers and the unsulfated structure. The expansion of this method may afford an avenue for the high throughput investigation of O-glycans.

Protein target quantification decision tree

The utility of mass spectrometry-(MS-) based proteomic platforms and their clinical applications have become an emerging field in proteomics in recent years. Owing to its selectivity and sensitivity, MS has become a key technological platform in proteomic research. Using this platform, a large number of potential biomarker candidates for specific diseases have been reported. However, due to lack of validation, none has been approved for use in clinical settings by the Food and Drug Administration (FDA). Successful candidate verification and validation will facilitate the development of potential biomarkers, leading to better strategies for disease diagnostics, prognostics, and treatment. With the recent new developments in mass spectrometers, high sensitivity, high resolution, and high mass accuracy can be achieved. This greatly enhances the capabilities of protein biomarker validation. In this paper, we describe and discuss recent developments and applications of targeted proteomics methods for biomarker validation.

Rapid development of sensitive, high-throughput, quantitative and highly selective mass spectrometric targeted immunoassays for clinically important proteins in human plasma and serum

OBJECTIVES

The aim of this study was to develop high-throughput, quantitative and highly selective mass spectrometric, targeted immunoassays for clinically important proteins in human plasma or serum.

DESIGN AND METHODS

The described method coupled mass spectrometric immunoassay (MSIA), a previously developed technique for immunoenrichment on a monolithic microcolumn activated with an anti-protein antibody and fixed in a pipette tip, to selected reaction monitoring (SRM) detection and accurate quantification of targeted peptides, including clinically relevant sequence or truncated variants.

RESULTS

In this report, we demonstrate the rapid development of MSIA-SRM assays for sixteen different target proteins spanning seven different clinically important areas (including neurological, Alzheimer's, cardiovascular, endocrine function, cancer and other diseases) and ranging in concentration from pg/mL to mg/mL. The reported MSIA-SRM assays demonstrated high sensitivity (within published clinical ranges), precision, robustness and high-throughput as well as specific detection of clinically relevant isoforms for many of the target proteins. Most of the assays were tested with bona-fide clinical samples. In addition, positive correlations, (R2 0.67-0.87, depending on the target peptide), were demonstrated for MSIA-SRM assay data with clinical analyzer measurements of parathyroid hormone (PTH) and insulin growth factor 1 (IGF1) in clinical sample cohorts.

CONCLUSIONS

We have presented a practical and scalable method for rapid development and deployment of MS-based SRM assays for clinically relevant proteins and measured levels of the target analytes in bona fide clinical samples. The method permits the specific quantification of individual protein isoforms and addresses the difficult problem of protein heterogeneity in clinical proteomics applications.

Tissue proteomics in pancreatic cancer study: discovery, emerging technologies, and challenges

Pancreatic cancer is a highly lethal disease that is difficult to diagnose and treat. The advances in proteomics technology, especially quantitative proteomics, have stimulated a great interest in applying this technology for pancreatic cancer study. A variety of tissue proteomics approaches have been applied to investigate pancreatic cancer and the associated diseases. These studies were carried out with various goals, aiming to better understand the molecular mechanisms underlying pancreatic tumorigenesis, to improve therapeutic treatment and to identify cancer associated protein signatures, signaling events as well as interactions between cancer cells and tumor microenvironment. Here, we provide an overview on the tissue proteomics studies of pancreatic cancer reported in the past few years in light of discovery and technology development.

Unraveling the different proteomic platforms

This review is addressed to scientists working outside the field of proteomics and wishes to shed a light on the possibility offered by the latest proteomics strategies. Bottom-up and top-down platforms are critically examined outlining advantages and limitations of their application to qualitative and quantitative investigations. Discovery, directed and targeted proteomics as different options for the management of the MS instrument are defined emphasizing their integration in the experimental plan to accomplish meaningful results. The issue of data validation is analyzed and discussed. The most common qualitative proteomic platforms are described, with a particular emphasis on enrichment methods to elucidate PTMs codes (i.e. ubiquitin and histone codes). Label-free and labeled methods for relative and absolute quantification are critically compared. The possible contribution of proteomics platforms to the transition from structural proteomics to functional proteomics (study of the functional connections between different proteins) and to the challenging system biology (integrated study of all the functional cellular functions) is also briefly discussed.