Achieving in-depth proteomics profiling by mass spectrometry

Benchmarking Non-Targeted Metabolomics Using Yeast-Derived Libraries

Non-targeted analysis by high-resolution mass spectrometry (HRMS) is an essential discovery tool in metabolomics. To date, standardization and validation remain a challenge. Community-wide accepted cost-effective benchmark materials are lacking. In this work, we propose yeast (Pichia pastoris) extracts derived from fully controlled fermentations for this purpose. We established an open-source metabolite library of >200 identified metabolites based on compound identification by accurate mass, matching retention times, and MS/MS, as well as a comprehensive literature search. The library includes metabolites from the classes of (1) organic acids and derivatives (2) nucleosides, nucleotides, and analogs, (3) lipids and lipid-like molecules, (4) organic oxygen compounds, (5) organoheterocyclic compounds, (6) organic nitrogen compounds, and (7) benzoids at expected concentrations ranges of sub-nM to µM. As yeast is a eukaryotic organism, key regulatory elements are highly conserved between yeast and all annotated metabolites were also reported in the human metabolome database (HMDB). Orthogonal state-of-the-art reversed-phase (RP-) and hydrophilic interaction chromatography mass spectrometry (HILIC-MS) non-targeted analysis and authentic standards revealed that 104 out of the 206 confirmed metabolites were reproducibly recovered and stable over the course of three years when stored at −80 °C. Overall, 67 out of these 104 metabolites were identified with comparably stable areas over all three yeast fermentation and are the ideal starting point for benchmarking experiments. The provided yeast benchmark material enabled not only to test for the chemical space and coverage upon method implementation and developments but also allowed in-house routines for instrumental performance tests. Transferring the quality control strategy of proteomics workflows based on the number of protein identification in HeLa extracts, metabolite IDs in the yeast benchmarking material can be used as metabolomics quality control. Finally, the benchmark material opens new avenues for batch-to-batch corrections in large-scale non-targeted metabolomics studies.

The Lymphatic Fluid

This review will highlight our current understanding of the formation, circulation, and immunological role of lymphatic fluid. The formation of the extracellular fluid depends on the net balance between the hydrostatic and osmotic pressure gradients effective in the capillary beds. Lymph originates from the extracellular fluid and its composition combines the ultrafiltrated plasma proteins with the proteome generated by the metabolic activities of each parenchymal tissue. Several analyses have indicated how the lymph composition reflects the organs' physiological and pathological states. The collected lymphatic fluid moves from the capillaries into progressively larger collectors toward the draining lymph node aided by the lymphangion contractility and unidirectional valves, which prevent backflow. The proteomic composition of the lymphatic fluid is reflected in the MHC II peptidome presented by nodal antigen-presenting cells. Taken together, the past few years have generated new interest in the formation, transport, and immunological role of the lymphatic fluid.

Stressor-induced proteome alterations in zebrafish: a meta-analysis of response patterns

Proteomics approaches are being increasingly applied in ecotoxicology on the premise that the identification of specific protein expression changes in response to a particular chemical would allow elucidation of the underlying molecular pathways leading to an adverse effect. This in turn is expected to promote the development of focused testing strategies for specific groups of toxicants. Although both gel-based and gel-free global characterization techniques provide limited proteome coverage, the conclusions regarding the cellular processes affected are still being drawn based on the few changes detected. To investigate how specific the detected responses are, we analyzed a set of studies that characterized proteome alterations induced by various physiological, chemical and biological stressors in zebrafish, a popular model organism. Our analysis highlights several proteins and protein groups, including heat shock and oxidative stress defense proteins, energy metabolism enzymes and cytoskeletal proteins, to be most frequently identified as responding to diverse stressors. In contrast, other potentially more specifically responding protein groups are detected much less frequently. Thus, zebrafish proteome responses to stress reported by different studies appear to depend mostly on the level of stress rather than on the specific stressor itself. This suggests that the most broadly used current proteomics technologies do not provide sufficient proteome coverage to allow in-depth investigation of specific mechanisms of toxicant action. We suggest that the results of any differential proteomics experiment performed with zebrafish should be interpreted keeping in mind the list of the most frequent responders that we have identified. Similar reservations should apply to any other species where proteome responses are analyzed by global proteomics methods. Careful consideration of the reliability and significance of observed changes is necessary in order not to over-interpret the experimental results and to prevent the proliferation of false positive linkages between the chemical and the cellular functions it perturbs. We further discuss the implications of the identified "top lists" of frequently responding proteins and protein families, and suggest further directions for proteomics research in ecotoxicology. Apart from improving the proteome coverage, further research should focus on defining the significance of the observed stress response patterns for organism phenotypes and on searching for common upstream regulators that can be targeted by specific assays.

Beyond the Western front: targeted proteomics and organelle abundance profiling

The application of westerns or immunoblotting techniques for assessing the composition, dynamics, and purity of protein extracts from plant material has become common practice. While the approach is reproducible, can be readily applied and is generally considered robust, the field of plant science suffers from a lack of antibody variety against plant proteins. The development of approaches that employ mass spectrometry to enable both relative and absolute quantification of many hundreds of proteins in a single sample from a single analysis provides a mechanism to overcome the expensive impediment in having to develop antibodies in plant science. We consider it an opportune moment to consider and better develop the adoption of multiple reaction monitoring (MRM)-based analyses in plant biochemistry.

Global proteomic assessment of the classical protein-tyrosine phosphatome and "Redoxome"

Protein-tyrosine phosphatases (PTPs), along with protein-tyrosine kinases, play key roles in cellular signaling. All Class I PTPs contain an essential active site cysteinyl residue, which executes a nucleophilic attack on substrate phosphotyrosyl residues. The high reactivity of the catalytic cysteine also predisposes PTPs to oxidation by reactive oxygen species, such as H(2)O(2). Reversible PTP oxidation is emerging as an important cellular regulatory mechanism and might contribute to diseases such as cancer. We exploited these unique features of PTP enzymology to develop proteomic methods, broadly applicable to cell and tissue samples, that enable the comprehensive identification and quantification of expressed classical PTPs (PTPome) and the oxidized subset of the PTPome (oxPTPome). We find that mouse and human cells and tissues, including cancer cells, display distinctive PTPomes and oxPTPomes, revealing additional levels of complexity in the regulation of protein-tyrosine phosphorylation in normal and malignant cells.

Gain and loss of extracellular molecules in sporadic inclusion body myositis and polymyositis--a proteomics-based study

Sporadic inclusion body myositis (sIBM) contains non-necrotic myofibers that are surrounded and/or invaded by inflammatory cells. In this study we aimed to identify selective molecules that are present at this site. Myofibers of four biopsies of sIBM that were surrounded and/or invaded by inflammatory cells were microdissected, pooled and profiled by proteomic studies using mass spectrometry. Normal skeletal muscle tissue served as control. Based on the table of proteins that were detected in sIBM only, we selected nine extracellular matrix molecules and validated the results performing immunofluorescence. Seven out of nine proteins that were detected in sIBM by mass spectrometry showed different immunohistochemical results in myositis and normal controls. Of these, the small leucine-rich repeat proteins proline arginine-rich end leucine-rich repeat protein (PRELP) and biglycan were deposited precisely at myofibers surrounded and/or invaded by inflammatory cells both in sIBM and polymyositis. The basement membrane (BM) molecules merosin, perlecan, nidogen-2 and collagen IV were variably destroyed or increased at these sites. P component, which ensheathed all myofibers in normal controls, was absent from invaded myofibers. Similar to BM remodeling, the specific deposition of PRELP and biglycan may represent a mechanism to defend against immune attack. Loss of P component may affect the anchorage of the myofiber in the endomysium.

Using proteomics to study sexual reproduction in angiosperms

While a relative latecomer to the postgenomics era of functional biology, the application of mass spectrometry-based proteomic analysis has increased exponentially over the past 10 years. Some of this increase is the result of transition of chemists, physicists, and mathematicians to the study of biology, and some is due to improved methods, increased instrument sensitivity, and better techniques of bioinformatics-based data analysis. Proteomic Biological processes are typically studied in isolation, and seldom are efforts made to coordinate results obtained using structural, biochemical, and molecular-genetic strategies. Mass spectrometry-based proteomic analysis can serve as a platform to bridge these disparate results and to additionally incorporate both temporal and anatomical considerations. Recently, proteomic analyses have transcended their initial purely descriptive applications and are being employed extensively in studies of posttranslational protein modifications, protein interactions, and control of metabolic networks. Herein, we provide a brief introduction to sample preparation, comparison of gel-based versus gel-free methods, and explanation of data analysis emphasizing plant reproductive applications. We critically review the results from the relatively small number of extant proteomics-based analyses of angiosperm reproduction, from flowers to seedlings, and speculate on the utility of this strategy for future developments and directions.

Functional analysis of proteins and protein species using shotgun proteomics and linear mathematics

Covalent post-translational modification of proteins is the primary modulator of protein function in the cell. It greatly expands the functional potential of the proteome compared to the genome. In the past few years shotgun proteomics-based research, where the proteome is digested into peptides prior to mass spectrometric analysis has been prolific in this area. It has determined the kinetics of tens of thousands of sites of covalent modification on an equally large number of proteins under various biological conditions and uncovered a transiently active regulatory network that extends into diverse branches of cellular physiology. In this review, we discuss this work in light of the concept of protein speciation, which emphasizes the entire post-translationally modified molecule and its interactions and not just the modification site as the functional entity. Sometimes, particularly when considering complex multisite modification, all of the modified molecular species involved in the investigated condition, the protein species must be completely resolved for full understanding. We present a mathematical technique that delivers a good approximation for shotgun proteomics data.

Emerging affinity-based techniques in proteomics

Proteomes of interest, such as the human proteome, have such complexity that no single technique is adequate for the complete analysis of the constituents. Depending on the goal (e.g., identification of a novel protein vs measurement of the level of a known protein), the tools required can vary significantly. While existing methods provide valuable information, their limitations drive the development of complementary, innovative methods to achieve greater breadth of coverage, dynamic range or specificity of analysis. We will discuss affinity-based methods and their applications, focusing on their unique advantages. In addition, we will describe emerging methods with potential value to proteomics, as well as the challenges that remain for proteomic studies.

Mass spectrometry based proteomics profiling as diagnostic tool in oncology: current status and future perspective

Proteomics analysis has been heralded as a novel tool for identifying new and specific biomarkers that may improve diagnosis and monitoring of various disease states. Recent years have brought a number of proteomics profiling technologies. Although proteomics profiling has resulted in the detection of disease-associated differences and modification of proteins, current proteomics technologies display certain limitations that are hampering the introduction of these new technologies into clinical laboratory diagnostics and routine applications. In this review, we summarize current advances in mass spectrometry based biomarker discovery. The promises and challenges of this new technology are discussed with particular emphasis on diagnostic perspectives of mass-spectrometry based proteomics profiling for malignant diseases.

Exploring DNA-binding proteins with in vivo chemical cross-linking and mass spectrometry

DNA-binding proteins are very important constituents of proteomes of all species and play crucial roles in transcription, DNA replication, recombination, repair, and other activities associated with DNA. Although a number of DNA-binding proteins have been identified, many proteins involved in gene regulation and DNA repair are likely still unknown because of their dynamic and/or weak interactions with DNA. In this report, we described an approach for the comprehensive identification of DNA-binding proteins with in vivo formaldehyde cross-linking and LC-MS/MS. DNA-binding proteins could be purified via the isolation of DNA-protein complexes and released from the complexes by reversing the cross-linking. By using this method, we were able to identify more than one hundred DNA-binding proteins, such as proteins involved in transcription, gene regulation, DNA replication and repair, and a large number of proteins that are potentially associated with DNA and DNA-binding proteins. This method should be generally applicable to the investigation of other nucleic acid-binding proteins, and hold great potential in the comprehensive study of gene regulation, DNA damage response and repair, as well as many other critical biological processes at proteomic level.

Perspectives for imaging mass spectrometry in the proteomics landscape

A number of techniques are used in the field of proteomics that can be combined to get the most molecular information from a specific biological sample, fluid or tissue. Imaging techniques are often used to obtain local information from tissue samples. However, imaging experiments are often staining experiments, which rely on specific or aspecific interactions between fluorescent markers and pre-defined (families of) peptide or protein. Therefore, imaging is often used as a screening or validation tool for the local presence of proteins that have been identified by other means. Imaging mass spectrometry (IMS) combines the advantages of MS and microscopy in a single experiment. It is a technique that does not require any labeling of the analytes and provides a high multiplexing capability combined with the potential for analyte identification. It enables simultaneous detection of potentially all peptides and proteins present at a tissue surface and is used for the determination and identification of tissue-specific disease markers. The workflows of IMS experiments closely resemble those of conventional proteomics. In this review, we describe IMS experiments step-by-step to position and evaluate the role of IMS in a comparative proteomics landscape. We illustrate in a concise review that IMS is a true discovery oriented tool for proteomics that seamlessly integrates in conventional proteomics workflows and can be perceived as either an alternative or complementary proteomics technique.

Exploiting proteomic data for genome annotation and gene model validation in Aspergillus niger

BACKGROUND

Proteomic data is a potentially rich, but arguably unexploited, data source for genome annotation. Peptide identifications from tandem mass spectrometry provide prima facie evidence for gene predictions and can discriminate over a set of candidate gene models. Here we apply this to the recently sequenced Aspergillus niger fungal genome from the Joint Genome Institutes (JGI) and another predicted protein set from another A.niger sequence. Tandem mass spectra (MS/MS) were acquired from 1d gel electrophoresis bands and searched against all available gene models using Average Peptide Scoring (APS) and reverse database searching to produce confident identifications at an acceptable false discovery rate (FDR).

RESULTS

405 identified peptide sequences were mapped to 214 different A.niger genomic loci to which 4093 predicted gene models clustered, 2872 of which contained the mapped peptides. Interestingly, 13 (6%) of these loci either had no preferred predicted gene model or the genome annotators' chosen "best" model for that genomic locus was not found to be the most parsimonious match to the identified peptides. The peptides identified also boosted confidence in predicted gene structures spanning 54 introns from different gene models.

CONCLUSION

This work highlights the potential of integrating experimental proteomics data into genomic annotation pipelines much as expressed sequence tag (EST) data has been. A comparison of the published genome from another strain of A.niger sequenced by DSM showed that a number of the gene models or proteins with proteomics evidence did not occur in both genomes, further highlighting the utility of the method.

Recent advances in atherosclerosis-based proteomics: new biomarkers and a future perspective

Vascular proteomics is providing two main types of data: proteins that actively participate in vascular pathophysiological processes and novel protein candidates that can potentially serve as useful clinical biomarkers. Although both types of proteins can be identified by similar proteomic strategies and methods, it is important to clearly distinguish biomarkers from mediators of disease. A particular protein, or group of proteins, may participate in a pathogenic process but not serve as an effective biomarker. Alternatively, a useful biomarker may not mediate pathogenic pathways associated with disease (i.e., C-reactive protein). To date, there are no clear successful examples in which discovery proteomics has led to a novel useful clinical biomarker in cardiovascular diseases. Nevertheless, new sources of biomarkers are being explored (i.e., secretomes, circulating cells, exosomes and microparticles), an increasing number of novel proteins involved in atherogenesis are constantly described, and new technologies and analytical strategies (i.e., quantitative proteomics) are being developed to access low abundant proteins. Therefore, this presages a new era of discovery and a further step in the practical application to diagnosis, prognosis and early action by medical treatment of cardiovascular diseases.

Comparative analysis of proteome differential regulation during cell dedifferentiation in Arabidopsis

Cell dedifferentiation is a cell fate switching process in which differentiated cells undergo genome reprogramming to regain the competency of cell division and organ regeneration. The molecular mechanism underlying the cell dedifferentiation process remains obscure. In this report, we investigate the cell dedifferentiation process in Arabidopsis using a shotgun proteomics approach. A total of 758 proteins are identified by two or more matched peptides. Comparative analyses at four time points using two label-free methods reveal that 193 proteins display up-regulation and 183 proteins display down-regulation within 48 h. While the results of the two label-free quantification methods match well with each other, comparison with previously published 2-DE gel results reveal that label-free quantification results differ substantially from those of the 2-DE method for proteins with peptides common to multiple proteins, suggesting a limitation of the label-free methods in quantifying proteins with closely related family members in complex samples. Our results show that the shotgun approach and the traditional 2-DE gel approach complement each other in both protein identification and quantification. An interesting observation is that core histones and histone variants are subjected to extensive down-regulation, indicating that there is a dramatic change in the chromatin during cell differentiation.

Sperm chromatin: fertile grounds for proteomic discovery of clinical tools

Sperm are remarkably complex cells with a singularly important mission: to deliver paternal DNA and its associated factors to the oocyte to start a new life. The integrity of sperm DNA is a keystone of reproductive success, which includes fertilization and embryonic development. In addition, the significance in these processes of proteins that associate with sperm DNA is increasingly being appreciated. In this review, we highlight proteomic studies that have identified sperm chromatin proteins with fertility roles that have been validated by molecular studies in model organisms or correlations in the clinic. Up to 50% of male-factor infertility cases in the clinic have no known cause and therefore no direct treatment. In-depth study of the molecular basis of infertility has great potential to inform the development of sensitive diagnostic tools and effective therapies that will address this incongruity. Because sperm rely on testis-specific protein isoforms and post-translational modifications for their development and function, sperm-specific processes are ideal for proteomic explorations that can bridge the research lab and fertility clinic.

Sequential interval motif search: unrestricted database surveys of global MS/MS data sets for detection of putative post-translational modifications

Tandem mass spectrometry is the prevailing approach for large-scale peptide sequencing in high-throughput proteomic profiling studies. Effective database search engines have been developed to identify peptide sequences from MS/MS fragmentation spectra. Since proteins are polymorphic and subject to post-translational modifications (PTM), however, computational methods for detecting unanticipated variants are also needed to achieve true proteome-wide coverage. Different from existing "unrestrictive" search tools, we present a novel algorithm, termed SIMS (for Sequential Motif Interval Search), that interprets pairs of product ion peaks, representing potential amino acid residues or "intervals", as a means of mapping PTMs or substitutions in a blind database search mode. An effective heuristic software program was likewise developed to evaluate, rank, and filter optimal combinations of relevant intervals to identify candidate sequences, and any associated PTM or polymorphism, from large collections of MS/MS spectra. The prediction performance of SIMS was benchmarked extensively against annotated reference spectral data sets and compared favorably with, and was complementary to, current state-of-the-art methods. An exhaustive discovery screen using SIMS also revealed thousands of previously overlooked putative PTMs in a compendium of yeast protein complexes and in a proteome-wide map of adult mouse cardiomyocytes. We demonstrate that SIMS, freely accessible for academic research use, addresses gaps in current proteomic data interpretation pipelines, improving overall detection coverage, and facilitating comprehensive investigations of the fundamental multiplicity of the expressed proteome.

A chemical approach for detecting sulfenic acid-modified proteins in living cells

Oxidation of the thiol functional group in cysteine (Cys-SH) to sulfenic (Cys-SOH), sulfinic (Cys-SO2H) and sulfonic acids (Cys-SO3H) is emerging as an important post-translational modification that can activate or deactivate the function of many proteins. Changes in thiol oxidation state have been implicated in a wide variety of cellular processes and correlate with disease states but are difficult to monitor in a physiological setting because of a lack of experimental tools. Here, we describe a method that enables live cell labeling of sulfenic acid-modified proteins. For this approach, we have synthesized the probe DAz-1, which is chemically selective for sulfenic acids and cell permeable. In addition, DAz-1 contains an azide chemical handle that can be selectively detected with phosphine reagents via the Staudinger ligation for identification, enrichment and visualization of modified proteins. Through a combination of biochemical, mass spectrometry and immunoblot approaches we characterize the reactivity of DAz-1 and highlight its utility for detecting protein sulfenic acids directly in mammalian cells. This novel method to isolate and identify sulfenic acid-modified proteins should be of widespread utility for elucidating signaling pathways and regulatory mechanisms that involve oxidation of cysteine residues.

Recent advances in chemical proteomics: exploring the post-translational proteome

Identification and quantification of multiple proteins from complex mixtures is a central theme in post-genomic biology. Despite recent progress in high-throughput proteomics, proteomic analysis of post-translationally modified (PTM) proteins remains particularly challenging. This mini-review introduces the emerging field of chemical proteomics and reviews recent advances in chemical proteomic technology that are offering striking new insights into the functional biology of post-translational modification.

Biochemical approaches for discovering protein-protein interactions

Protein-protein interactions or protein complexes are integral in nearly all cellular processes, ranging from metabolism to structure. Elucidating both individual protein associations and complex protein interaction networks, while challenging, is an essential goal of functional genomics. For example, discovering interacting partners for a 'protein of unknown function' can provide insight into actual function far beyond what is possible with sequence-based predictions, and provide a platform for future research. Synthetic genetic approaches such as two-hybrid screening often reveal a perplexing array of potential interacting partners for any given target protein. It is now known, however, that this type of anonymous screening approach can yield high levels of false-positive results, and therefore putative interactors must be confirmed by independent methods. In vitro biochemical strategies for identifying interacting proteins are varied and time-honored, some being as old as the field of protein chemistry itself. Herein we discuss five biochemical approaches for isolating and characterizing protein-protein interactions in vitro: co-immunoprecipitation, blue native gel electrophoresis, in vitro binding assays, protein cross-linking, and rate-zonal centrifugation. A perspective is provided for each method, and where appropriate specific, trial-tested methods are included.

Nanotechnology in proteomics

In genomics, the ability to amplify rare transcripts has enabled rapid advances in the understanding of gene expression patterns in human disease. The inability to increase the copy number and to detect the signal of rare proteins as unique species in biological samples has hindered the ability of proteomics to dissect human disease with the same complexity as genomic analyses. Advances in nanotechnology have begun to allow researchers to identify low-abundance proteins in samples through techniques that rely upon both nanoparticles and nanoscale devices. Coupled with rapid advances made in protein identification and isolation over the past decade, currently available technology enables more effective multiplexing and improved signal-to-noise, which enhances detection of low-abundance proteins in cellular and tissue lysates significantly. Techniques, including nanowires, nanocantilevers, bio-barcoding and surface-enhanced Raman spectroscopy, permit the detection of proteins into the low attomolar range, where many biologically important cellular processes occur. In this review, we summarize several such techniques, highlight their implementation in current protein research and comment on their potential role in future proteomic investigations and biomedical applications.

ImmunoCell-Array: a novel technology for pathway discovery and cell profiling

A major challenge in drug discovery is the definition of the activity of therapeutic compounds before they enter clinical trials. Currently, many tools are available to profile drug response at a multiparametric level. Furthermore, the novel discipline of systems biology is offering interpretative cues to the amount of data generated by the so-called omics technologies. Nonetheless, novel approaches are needed to comprehensively evaluate drug response. This review will describe a recent technology for protein profiling, the ImmunoCell-Array, which, in to the authors' opinion, can enter the scenario of profiling technologies with the goal of offering a comprehensive description of proteome dynamics in a cellular context.

Lost in translation: five grand challenges for proteomic biomarker discovery

The biomedical community has the imperative to develop reliable, clinically relevant and generalizable bioassays that can be used to accurately recognize those individuals with early-stage disease or those patients who will respond to therapy, with the ultimate aim of achieving individualized medicine. In recent years, increasingly sophisticated proteomic screening technologies have been introduced, providing the biomedical community with a valuable new approach for the systematic discovery and validation of novel diagnostic, prognostic and therapeutic tools. Nevertheless, the complexity of the cellular milieu wherein a variety of macromolecules interact in dynamic fashion, combined with the complex clinical manifestation of chronic pathologies and widespread diversity of patient populations, mean that universal biomarkers will not be easily developed. In this review, the five key challenges that must be surmounted in order to advance the clinical impact of this nascent field are described, and plausible solutions based on the authors' own ongoing proteomic profiling of cardiovascular disease is outlined.

The ongoing evolution of proteomics in malignancy

The complementary fields of genomics and proteomics offer insights into the molecular mechanisms of diseases. While genomics seeks to define our genetic substrate, proteomics explores the structure and function of proteins, which are the end effectors of our genes. Proteomics has been revolutionized in the past decade by the application of techniques such as protein arrays, two-dimensional gel electrophoresis, and mass spectrometry. These techniques have tremendous potential for biomarker development, target validation, diagnosis, prognosis, and optimization of treatment in medical care, especially in the field of clinical oncology. We will discuss innovations in proteomic technologies and highlight their prospective applications to patient care.

Development of surface plasmon resonance mass spectrometry array platform

Protein microarrays are the format of choice for high-throughput, high-content protein interaction analysis. In most of the array formats, reporter molecules are used in multistep detection of the protein interactions. Among the few existing label-free detection approaches, surface plasmon resonance (SPR) and mass spectrometry (MS) stand out as most promising for utilization in protein microarrays, albeit both have been used only sporadically for high-content protein arrays. Shown here for the first time is the combination of SPR and MS detection on a single high-content protein microarray. Antibodies to five human plasma proteins were arrayed in a 10 x 10 spot arrangement on a chemically activated gold-coated glass chip. Binding of proteins to their corresponding antibodies was monitored via SPR imaging across the entire surface of the chip. Following protein affinity retrieval, the chip was overlaid with MALDI matrix and MS analyzed, producing protein-specific mass spectra from distinct spots on the array. The SPR-MS dual detection is well suited for high-content protein microarrays and comprehensive protein analysis-from quantitative assessment of the protein concentration to detection of structural protein variants arising from genetic variations and postexpression processing.

Comparative evaluation of tandem MS search algorithms using a target-decoy search strategy

Peptide identification of tandem mass spectra by a variety of available search algorithms forms the foundation for much of modern day mass spectrometry-based proteomics. Despite the critical importance of proper evaluation and interpretation of the results generated by these algorithms there is still little consistency in their application or understanding of their similarities and differences. A survey was conducted of four tandem mass spectrometry peptide identification search algorithms, including Mascot, Open Mass Spectrometry Search Algorithm, Sequest, and X! Tandem. The same input data, search parameters, and sequence library were used for the searches. Comparisons were based on commonly used scoring methodologies for each algorithm and on the results of a target-decoy approach to sequence library searching. The results indicated that there is little difference in the output of the algorithms so long as consistent scoring procedures are applied. The results showed that some commonly used scoring procedures may lead to excessive false discovery rates. Finally an alternative method for the determination of an optimal cutoff threshold is proposed.