A mass spectrometric journey into protein and proteome research

Analysis of natural organic matter via fourier transform ion cyclotron resonance mass spectrometry: an overview of recent non-petroleum applications

Among the different techniques for mass analysis, ultra-high-resolution Fourier transform ion cyclotron resonance (FTICR) is the method of choice for highly complex samples, as it offers unrivaled mass accuracy and resolving power, combined with a high degree of flexibility in hybrid instruments as well as for ion activation techniques. FTICR instruments are readily embraced by the biological and biomedical research communities and applied over a wide range of applications for the analysis of biomolecules such as carbohydrates, lipids, nucleic acids, and proteins. In the field of natural organic matter (NOM) analysis, petroleum-related studies currently dominate FTICR-MS applications. Recently, however, there is a growing interest in developing high-performance MS methods for the characterization of NOM samples from natural aquatic and terrestrial environments. Here, we present an overview of FTICR-MS techniques for complex, non-petroleum NOM samples, including data analysis and novel tandem mass spectrometry (MS/MS) methods for structural classifications. © 2020 The Authors. Mass Spectrometry Reviews published by John Wiley & Sons Ltd.

Technique development of high-throughput and high-sensitivity sample preparation and separation for proteomics

Sample preparation and separation methods determine the sensitivity and the quantification accuracy of the proteomics analysis. This article covers a comprehensive review of the recent technique development of high-throughput and high-sensitivity sample preparation and separation methods in proteomics research.

Investigation of cattle plasma proteome in response to pain and inflammation using next generation proteomics technique, SWATH-MS

Pain assessment in farm animals has primarily relied on a combination of behavioral and physiological responses, although these are relatively subjective and difficult to quantify. It is essential to develop more effective biomarkers of pain in production animals since they are frequently exposed to routine surgical husbandry procedures. More effective biomarkers of pain would improve welfare, limit the loss of productivity associated with pain and permit better assessment of analgesics. This study aimed to investigate the use of a modern mass spectrometry data independent acquisition strategy, termed Sequential Window Acquisition of All Theoretical Mass Spectra (SWATH-MS), to detect candidate protein biomarkers that are known to associate with nociceptive and inflammatory processes in cattle, which could then be used to assess the efficacy of potential analgesics. Calves were randomly divided into two groups that were either surgically dehorned or subjected to restraint stress, without provision of anaesthesia or analgesia in accordance with current industry standards. Samples were analysed before and after dehorning at multiple timepoints. Significant changes in protein concentrations were detected predominantly at 24 and 96 h following dehorning, including kininogens, proteins associated with the coagulation and complement cascades and serine protease inhibitors. Gene ontology analysis revealed that the identified candidate biomarkers were associated with stress, wound healing, immune response, blood coagulation and the inflammatory and acute phase responses, which could be expected following surgical damage to tissues, but can now be more objectively assessed. These results offer more definitive and quantitative monitoring of response to tissue injury induced pain and inflammation.

Mimicking LysC Proteolysis by 'Arginine-Modification-cum-Trypsin digestion': Comparison of Bottom-Up & Middle-Down Proteomic Approaches by ESI-QTOF-MS

BACKGROUND

Middle-down (MD) proteomics is an emerging approach for reliable identification of post- translational modifications and isoforms, as this approach focuses on proteolytic peptides containing > 25 - 30 amino acid residues (a.a.r.), which are longer than typical tryptic peptides. Such longer peptides can be obtained by AspN, GluC, LysC proteases. Additionally, some special proteases were developed specifically to effect MD approach, e.g., OmpT, Sap9, etc. However, these proteases are expensive. Herein we report a cost-effective strategy, 'arginine modification-cum trypsin digestion', which can produce longer tryptic peptides resembling LysC peptides derived from proteins.

OBJECTIVE

To obtain proteolytic peptides that resemble LysC peptides, by using 'trypsin', which is an less expensive protease.

METHODS

This strategy is based on the simple principle that trypsin cannot act at the C-termini of those arginines in proteins, whose sidechain guanidine groups are modified by 1,2-cyclohexanedione or phenylglyoxal.

RESULTS

As a proof of concept, we demonstrate this strategy on four models: β-casein (bovine), β- lactoglobulin (bovine), ovalbumin (chick) and transferrin (human), by electrospray ionization-mass spectrometry (ESI-MS) involving hybrid quadrupole time-of-flight. From the ESI-MS of these models, we obtained several arginine modified tryptic peptides, whose lengths are in the range, 30 - 60 a.a.r. The collision-induced dissociation MS/MS characteristics of some of the arginine modified longer tryptic peptides are compared with the unmodified standard tryptic peptides.

CONCLUSION

The strategy followed in this proof-of-concept study, not only helps in obtaining longer tryptic peptides that mimic LysC proteolytic peptides, but also facilitates in enhancing the probability of missed cleavages by the trypsin. Hence, this method aids in evading the possibility of obtaining very short peptides that are < 5 - 10 a.a.r. Therefore, this is indeed an cost-effective alternative/substitute for LysC proteolysis and in turn, for those MD proteomic studies that utilize LysC. Additionally, this methodology can be fruitful for mass spectrometry based de novo protein and peptide sequencing.

FPTMS: Frequency-based approach to identify the peptide from the low-energy collision-induced dissociation tandem mass spectra

The database search method is a widely accepted method to assign a peptide to the tandem mass spectra. In this study, a new flexible method- FPTMS is introduced to interpret the tandem mass spectra with the known peptide sequences in a protein database. Here the frequency of occurrence of fragment ion peaks extracted from the extensive spectral library is used to predict the theoretical tandem mass spectra of the peptides. The dot product scoring and windowed-xcorr scoring methods were implemented to score the experimental spectrum against the theoretical peptide spectra. Windowed-xcorr is introduced to tackle the mass errors and the cleavage position of the fragmentation process. The new method with windowed-xcorr shows an improved identification rate compared to the existing search engines Crux-Tide and X!Tandem at 1% False Discovery Rate (FDR) for the dataset considered in this study. SIGNIFICANCE: Identifying or sequencing of the peptide from tandem mass spectra is an important application in mass spectrometry-based proteomics. Collision-induced dissociation (CID) fragmentation spectra have been widely used to develop a peptide identification algorithm using database search strategy. CID fragmentation behavior is a complex process and found to have dependency on the sequences of peptide, charge state, and residue content. The inclusion of more features of peptide fragmentation behavior and adaptable scoring algorithm improves the efficiency of the peptide identification algorithm.

Coupling 193 nm Ultraviolet Photodissociation and Ion Mobility for Sequence Characterization of Conformationally-Selected Peptides

Ultraviolet photodissociation (UVPD) has emerged as a useful technique for characterizing peptide, protein, and protein complex primary and secondary structure. 193 nm UVPD, specifically, enables extensive covalent fragmentation of the peptide backbone without the requirement of a specific side chain chromophore and with no precursor charge state dependence. We have modified a commercial quadrupole-ion mobility-time-of-flight (Q-IM-TOF) mass spectrometer to include 193 nm UVPD following ion mobility. Ion mobility (IM) is a gas-phase separation technique that enables separation of ions by their size, shape, and charge, providing an orthogonal dimension of separation to mass analysis. Following instrument modifications, we characterized the performance of, and information that could be generated from, this new setup using the model peptides substance P, melittin, and insulin chain B. These experiments show extensive fragmentation across the peptide backbone and a variety of ion types as expected from 193 nm UVPD. Additionally, y-2 ions (along with complementary a+2 and b+2 ions) N-terminal to proline were observed. Combining the IM separation and mobility gating capabilities with UVPD, we demonstrate the ability to accomplish both mass- and mobility-selection of bradykinin des-Arg9 and des-Arg1 peptides followed by complete sequence characterization by UVPD. The new capabilities of this modified instrument demonstrate the utility of combining IM with UVPD because isobaric species cannot be independently selected with a traditional quadrupole alone.

A Frequency-Based Approach to Predict the Low-Energy Collision-Induced Dissociation Fragmentation Spectra

Peptide identification algorithms rely on the comparison between the experimental tandem mass spectrometry spectrum and the theoretical spectrum to identify a peptide from the tandem mass spectra. Hence, it is important to understand the fragmentation process and predict the tandem mass spectra for high-throughput proteomics research. In this study, a novel method was developed to predict the theoretical ion trap collision-induced dissociation (CID) tandem mass spectra of the singly, doubly, and triply charged tryptic peptides. The fragmentation statistics of the ion trap CID spectra were used to predict the theoretical tandem mass spectra of the peptide sequence. The study estimated the relative cleavage frequency for each pair of adjacent amino acids along the peptide length. The study showed that the cleavage frequency can be directly used to predict the tandem mass spectra. The predicted spectra show a high correlation with the experimental spectra used in this study; 99.73% of the high-quality reference spectra have correlation scores greater than 0.8. The new method predicts the theoretical spectrum and correlates significantly better with the experimental spectrum as compared to the existing spectrum prediction tools OpenMS_Simulator, MS2PIP, and MS2PBPI, where only 80, 85.76, and 85.80% of the spectral count, respectively, has a correlation score greater than 0.8.

Multiplex targeted mass spectrometry assay for one-shot flavivirus diagnosis

Targeted proteomic mass spectrometry is emerging as a salient clinical diagnostic tool to track protein biomarkers. However, its strong analytical properties have not been exploited in the diagnosis and typing of flaviviruses. Here, we report the development of a sensitive and specific single-shot robust assay for flavivirus typing and diagnosis using targeted mass spectrometry technology. Our flavivirus parallel reaction monitoring assay (fvPRM) has the ability to track secreted flaviviral nonstructural protein 1 (NS1) over a broad diagnostic and typing window with high sensitivity, specificity, extendibility, and multiplexing capability. These features, pivotal and pertinent to efficient response toward flavivirus outbreaks, including newly emerging flavivirus strains, circumvent the limitations of current diagnostic assays. fvPRM thus carries high potential in positioning itself as a forerunner in delivering early and accurate diagnosis for disease management.

Toward multiomics-based next-generation diagnostics for precision medicine

Our healthcare system is experiencing a paradigm shift to precision medicine, aiming at an early prediction of individual disease risks and targeted interventions. Whole-genome sequencing is currently gaining momentum, as it has the potential to capture all classes of genetic variation, thus providing a more complete picture of the individual's genetic makeup, which could be utilized in genetic testing; however, this will also lead to difficulties in interpreting the test results, necessitating careful integration of genomic data with other layers of information, both molecular multiomics measurements of epigenome, transcriptome, proteome, metabolome and even microbiome, as well as comprehensive information on diet, lifestyle and environment. Overall, the translation of patient-specific data into actionable diagnostic tools will be a challenging task, requiring expertise from multiple disciplines, secure data sharing in large reference databases and a strong computational infrastructure.

Complementarity of Matrix- and Nanostructure-Assisted Laser Desorption/Ionization Approaches

In recent years, matrix-assisted laser desorption/ionization (MALDI) has become the main tool for the study of biological macromolecules, such as protein nano-machines, especially in the determination of their molecular masses, structure, and post-translational modifications. A key role in the classical process of desorption and ionization of the sample is played by a matrix, usually a low-molecular weight weak organic acid. Unfortunately, the interpretation of mass spectra in the mass range of below m/z 500 is difficult, and hence the analysis of low molecular weight compounds in a matrix-assisted system is an analytical challenge. Replacing the classical matrix with nanomaterials, e.g., silver nanoparticles, allows improvement of the selectivity and sensitivity of spectrometric measurement of biologically important small molecules. Nowadays, the nanostructure-assisted laser desorption/ionization (NALDI) approach complements the classic MALDI in the field of modern bioanalytics. In particular, the aim of this work is to review the recent advances in MALDI and NALDI approaches.

Illuminating the dark phosphoproteome

Protein phosphorylation is a major regulator of protein function and biological outcomes. This was first recognized through functional biochemical experiments, and in the past decade, major technological advances in mass spectrometry have enabled the study of protein phosphorylation on a global scale. This rapidly growing field of phosphoproteomics has revealed that more than 100,000 distinct phosphorylation events occur in human cells, which likely affect the function of every protein. Phosphoproteomics has improved the understanding of the function of even the most well-characterized protein kinases by revealing new downstream substrates and biology. However, current biochemical and bioinformatic approaches have only identified kinases for less than 5% of the phosphoproteome, and functional assignments of phosphosites are almost negligible. Notably, our understanding of the relationship between kinases and their substrates follows a power law distribution, with almost 90% of phosphorylation sites currently assigned to the top 20% of kinases. In addition, more than 150 kinases do not have a single known substrate. Despite a small group of kinases dominating biomedical research, the number of substrates assigned to a kinase does not correlate with disease relevance as determined by pathogenic human mutation prevalence and mouse model phenotypes. Improving our understanding of the substrates targeted by all kinases and functionally annotating the phosphoproteome will be broadly beneficial. Advances in phosphoproteomics technologies, combined with functional screening approaches, should make it feasible to illuminate the connectivity and functionality of the entire phosphoproteome, providing enormous opportunities for discovering new biology, therapeutic targets, and possibly diagnostics.

Characterization of the chondrocyte secretome in photoclickable poly(ethylene glycol) hydrogels

Poly(ethylene glycol) (PEG) hydrogels are highly tunable platforms that are promising cell delivery vehicles for chondrocytes and cartilage tissue engineering. In addition to characterizing the type of extracellular matrix (ECM) that forms, understanding the types of proteins that are secreted by encapsulated cells may be important. Thus, the objectives for this study were to characterize the secretome of chondrocytes encapsulated in PEG hydrogels and determine whether the secretome varies as a function of hydrogel stiffness and culture condition. Bovine chondrocytes were encapsulated in photoclickable PEG hydrogels with a compressive modulus of 8 and 46 kPa and cultured under free swelling or dynamic compressive loading conditions. Cartilage ECM deposition was assessed by biochemical assays and immunohistochemistry. The conditioned medium was analyzed by liquid chromatography-tandem mass spectrometry. Chondrocytes maintained their phenotype within the hydrogels and deposited cartilage-specific ECM that increased over time and included aggrecan and collagens II and VI. Analysis of the secretome revealed a total of 64 proteins, which were largely similar among all experimental conditions. The identified proteins have diverse functions such as biological regulation, response to stress, and collagen fibril organization. Notably, many of the proteins important to the assembly of a collagen-rich cartilage ECM were identified and included collagen types II(α1), VI (α1, α2, and α3), IX (α1), XI (α1 and α2), and biglycan. In addition, many of the other identified proteins have been reported to be present within cell-secreted exosomes. In summary, chondrocytes encapsulated within photoclickable PEG hydrogels secrete many types of proteins that diffuse out of the hydrogel and which have diverse functions, but which are largely preserved across different hydrogel culture environments. Biotechnol. Bioeng. 2017;114: 2096-2108. © 2017 Wiley Periodicals, Inc.

Locus-specific Retention Predictor (LsRP): A Peptide Retention Time Predictor Developed for Precision Proteomics

The precision prediction of peptide retention time (RT) plays an increasingly important role in liquid chromatography-tandem mass spectrometry (LC-MS/MS) based proteomics. Owing to the high reproducibility of liquid chromatography, RT prediction provides promising information for both identification and quantification experiment design. In this work, we present a Locus-specific Retention Predictor (LsRP) for precise prediction of peptide RT, which is based on amino acid locus information and Support Vector Regression (SVR) algorithm. Corresponding to amino acid locus, each peptide sequence was converted to a featured locus vector consisting of zeros and ones. With locus vector information from LC-MS/MS data sets, an SVR computational process was trained and evaluated. LsRP finally provided a prediction correlation coefficient of 0.95~0.99. We compared our method with two common predictors. Results showed that LsRP outperforms these methods and tracked up to 30% extra peptides in an extraction RT window of 2 min. A new strategy by combining LsRP and calibration peptide approach was then proposed, which open up new opportunities for precision proteomics.

Electron-based fragmentation methods in mass spectrometry: An overview

Tandem mass spectrometry (MS/MS) provides detailed information for structural characterization of biomolecules. The combination of electron capture dissociation (ECD) techniques with Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) often provides unique ion-electron reactions and fragmentation channels in MS/MS. ECD is often a complimentary, sometimes even a superior tool to conventional MS/MS techniques. This article is aimed at providing a short overview of ECD-based fragmentation techniques (ExD) and optimization of ECD experiments for FTICR mass analyzers. Most importantly, it is meant to pique the interest of potential users for this exciting research field. © 2015 Wiley Periodicals, Inc. Mass Spec Rev 36:4-15, 2017.

Proteomic-based biomarker discovery for development of next generation diagnostics

In the post-genome age, proteomics is receiving significant attention because they provide an invaluable source of biological structures and functions at the protein level. The search for disease-specific biomarkers for diagnostic and/or therapeutic applications is one of the areas that proteomics is having a significant impact. Thus, the identification of a "good" biomarker enables a more accurate early diagnosis and prognosis of disease. Rapid advancements in mass spectrometry (MS) instrumentation, liquid chromatography MS (LCMS), protein microarray technology, and other protein profiling methodologies have a substantial expansion of our toolbox to identify disease-specific protein and peptide biomarkers. This review covers a selection of widely used proteomic technologies for biomarker discovery. In addition, we describe the most commonly used approaches for diagnosis based on proteomic biomarkers and further discuss trends and critical challenges during development of cost-effective rapid diagnostic tests and microfluidic diagnostic systems based on proteomic biomarkers.

Structural analysis of small to medium-sized molecules by mass spectrometry after electron-ion fragmentation (ExD) reactions

Electron capture dissociation (ECD) is a tandem mass spectrometry (MS/MS) method that utilizes the interaction of ions and electrons. Its unique ability to preserve labile bonds distinguishes it from conventional threshold-based MS/MS methods, the most important of which is collision-induced dissociation (CID). During the last decade, ECD has opened up several new venues in protein analyses, for example top-down sequencing, identification of post-translational modifications, and characterization of protein-protein interactions. In recent years, a number of related dissociation techniques, so-called ExD techniques, particularly electron transfer dissociation (ETD), electron detachment dissociation (EDD), electron induced dissociation (EID), and negative electron transfer dissociation (NETD), have emerged and have extended the application range of ion-electron dissociations further. Importantly, ExD techniques have been applied beyond protein analyses, which is the focus of the current paper. This short introduction describes the application of ExD to small and medium-sized molecules and reviews important applications to natural products, biomedical compounds, synthetic molecules, crude oils, and environmental toxins.

Data processing in Fourier transform ion cyclotron resonance mass spectrometry

The Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometer intricately couples advanced physics, instrumentation, and electronics with chemical and particularly biochemical research. However, general understanding of the data processing methodologies used lags instrumentation, and most data processing algorithms we are familiar with in FT-ICR are not well studied; thus, professional skill and training in FT-ICR operation and data analysis is still the key to achieve high performance in FT-ICR. This review article is focused on FT-ICR data processing, and explains the procedures step-by-step for users with the goal of maximizing spectral features, such as mass accuracy, resolving power, dynamic range, and detection limits.

(Post-)genomics approaches in fungal research

To date, hundreds of fungal genomes have been sequenced and many more are in progress. This wealth of genomic information has provided new directions to study fungal biodiversity. However, to further dissect and understand the complicated biological mechanisms involved in fungal life styles, functional studies beyond genomes are required. Thanks to the developments of current -omics techniques, it is possible to produce large amounts of fungal functional data in a high-throughput fashion (e.g. transcriptome, proteome, etc.). The increasing ease of creating -omics data has also created a major challenge for downstream data handling and analysis. Numerous databases, tools and software have been created to meet this challenge. Facing such a richness of techniques and information, hereby we provide a brief roadmap on current wet-lab and bioinformatics approaches to study functional genomics in fungi.

Role and challenges of proteomics in pharma and biotech: technical, scientific and commercial perspective

Contemporary proteomics, currently in its exponential growth phase, is a bewildering array of tools. Proteomic methods are the result of a convergence of rapidly improving mass spectrometry technologies, protein chemistry and separation sciences, genomics and bioinformatics. Strides in improving proteomics technologies to map and measure proteomes and subproteomes are being made. However, no single proteomic platform appears ideally suited to address all research needs or accomplish ambitious goals satisfactorily. However, proteomics is in a unique position to contribute to protein discovery and to public health in terms of better biomarkers, diagnostics and treatment of disease. While the potential is great, many challenges and issues remain to be solved. Fundamental issues, such as biological variability, pre-analytic factors and analytical reproducibility, remain to be resolved. Neither an all-genetic approach nor an all-proteomic approach will solve biological complexity. Proteomics will be the foundation for constructing and extracting useful knowledge to pharma and biotech depicted in the following path: data --> structured data --> information --> information architecture --> knowledge --> useful knowledge.

Proteomic applications of protein quantification by isotope-dilution mass spectrometry

Over the decades, isotope-dilution mass spectrometry (IDMS) has been implemented extensively for accurate quantification of drugs, metabolites and peptides in body fluids and tissues. More recently, it has been extended for quantifying specific proteins in complex mixtures. In this extended methodology, proteins are subjected to endoprotease action and specific resultant peptides are quantified by using synthetic stable isotope-labeled standard (SIS) peptides and IDMS. This article outlines the utilities and applications of quantifying proteins by IDMS, emphasizing its complementary value to global survey-based proteomic studies. The potential of SIS peptides to provide quantitative insights into cell signaling is also highlighted, with specific examples. Finally, we propose several novel mass spectrometric data acquisition strategies for large-scale applications of IDMS and SIS peptides in systems biology and protein biomarker validation studies.

Proteomic analysis profile of engineered articular cartilage with chondrogenic differentiated adipose tissue-derived stem cells loaded polyglycolic acid mesh for weight-bearing area defect repair

The present study was designed to investigate the possibility of full-thickness defects repair in porcine articular cartilage (AC) weight-bearing area using chondrogenic differentiated autologous adipose-derived stem cells (ASCs) with a follow-up of 3 and 6 months, which is successive to our previous study on nonweight-bearing area. The isolated ASCs were seeded onto the phosphoglycerate/polylactic acid (PGA/PLA) with chondrogenic induction in vitro for 2 weeks as the experimental group prior to implantation in porcine AC defects (8 mm in diameter, deep to subchondral bone), with PGA/PLA only as control. With follow-up time being 3 and 6 months, both neo-cartilages of postimplantation integrated well with the neighboring normal cartilage and subchondral bone histologically in experimental group, whereas only fibrous tissue in control group. Immunohistochemical and toluidine blue staining confirmed similar distribution of COL II and glycosaminoglycan in the regenerated cartilage to the native one. A vivid remolding process with repair time was also witnessed in the neo-cartilage as the compressive modulus significantly increased from 70% of the normal cartilage at 3 months to nearly 90% at 6 months, which is similar to our former research. Nevertheless, differences of the regenerated cartilages still could be detected from the native one. Meanwhile, the exact mechanism involved in chondrogenic differentiation from ASCs seeded on PGA/PLA is still unknown. Therefore, proteome is resorted leading to 43 proteins differentially identified from 20 chosen two-dimensional spots, which do help us further our research on some committed factors. In conclusion, the comparison via proteome provided a thorough understanding of mechanisms implicating ASC differentiation toward chondrocytes, which is further substantiated by the present study as a perfect supplement to the former one in nonweight-bearing area.

Identification of fungal microorganisms by MALDI-TOF mass spectrometry

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has emerged as a reliable tool for fast identification and classification of microorganisms. In this regard, it represents a strong challenge to microscopic and molecular biology methods. Nowadays, commercial MALDI systems are accessible for biological research work as well as for diagnostic applications in clinical medicine, biotechnology and industry. They are employed namely in bacterial biotyping but numerous experimental strategies have also been developed for the analysis of fungi, which is the topic of the present review. Members of many fungal genera such as Aspergillus, Fusarium, Penicillium or Trichoderma and also various yeasts from clinical samples (e.g. Candida albicans) have been successfully identified by MALDI-TOF MS. However, there is no versatile method for fungi currently available even though the use of only a limited number of matrix compounds has been reported. Either intact cell/spore MALDI-TOF MS is chosen or an extraction of surface proteins is performed and then the resulting extract is measured. Biotrophic fungal phytopathogens can be identified via a direct acquisition of MALDI-TOF mass spectra e.g. from infected plant organs contaminated by fungal spores. Mass spectrometric peptide/protein profiles of fungi display peaks in the m/z region of 1000-20000, where a unique set of biomarker ions may appear facilitating a differentiation of samples at the level of genus, species or strain. This is done with the help of a processing software and spectral database of reference strains, which should preferably be constructed under the same standardized experimental conditions.

Personal genomes, quantitative dynamic omics and personalized medicine

The rapid technological developments following the Human Genome Project have made possible the availability of personalized genomes. As the focus now shifts from characterizing genomes to making personalized disease associations, in combination with the availability of other omics technologies, the next big push will be not only to obtain a personalized genome, but to quantitatively follow other omics. This will include transcriptomes, proteomes, metabolomes, antibodyomes, and new emerging technologies, enabling the profiling of thousands of molecular components in individuals. Furthermore, omics profiling performed longitudinally can probe the temporal patterns associated with both molecular changes and associated physiological health and disease states. Such data necessitates the development of computational methodology to not only handle and descriptively assess such data, but also construct quantitative biological models. Here we describe the availability of personal genomes and developing omics technologies that can be brought together for personalized implementations and how these novel integrated approaches may effectively provide a precise personalized medicine that focuses on not only characterization and treatment but ultimately the prevention of disease.

Profiling the proteome in renal transplantation

Improved monitoring of transplanted solid organs is one of the next crucial steps leading to an increase in both patient and allograft survival. This can be facilitated through one or a set of surrogate biomarker molecules that accurately and precisely indicate the health status of the transplanted organ. Recent developments in the field of high throughput "omic" methods including genomics and proteomics have facilitated robust and comprehensive analysis of genes and proteins. This development has stimulated efforts in the identification of effective and clinically applicable gene and protein biomarkers in solid organ transplantation, including kidney transplantation. Some achievements have been made through proteomics in terms of profiling proteins and identification of potential biomarkers. However, the road to a successful biomarker discovery and its clinical implementation has proved to be challenging, requiring a number of key issues to be addressed. Such issues are: the lack of widely accepted protocols, difficulty in sample processing and transportation and a lack of collaborative efforts to achieve significant sample sizes in clinical studies. In this review using our area of expertise, we describe the current strategies used for proteomic-based biomarker discovery in renal transplantation, discuss inherent issues associated with these efforts and propose better strategies for successful biomarker discovery.

Differences in the secretome of cartilage explants and cultured chondrocytes unveiled by SILAC technology

The main goal of our study was to analyze and compare the profiles of secreted proteins from adult human articular chondrocytes in monolayers, and cartilage explants in culture, using a de novo protein labeling approach. Stable isotope labeling of proteins in culture was used to differentiate between chondrocyte-derived proteins and other preexisting matrix-derived components, or proteins coming from serum or synovial fluids. Proteins in culture supernatants were resolved by one-dimensional SDS-PAGE electrophoresis, and analyzed in tandem with LC/MS-MS (liquid chromatography/double mass spectrometry). Results from stable isotope labeling with amino acids in cell culture (SILAC) were validated by specific immunoblotting of four relevant proteins identified in the secretion media. After 8-10 days of culture, over 90% of proteins secreted during monolayer growth contained (13)C(6)-Arg and (13)C(6)-Lys. Nonlabeled proteins corresponded mostly to plasma-associated proteins, indicating background contamination of medium with serum remnants. The majority of the secreted proteins in 2D cultures were extracellular matrix components and matrix regulators, along with some inflammatory agents and metabolic enzymes. In explants, only 25%-30% of proteins were labeled with heavy amino acids, corresponding to matrix regulators and carrier molecules. Nonlabeled proteins corresponded primarily to structural matrix components. In qualitative terms, all labeled proteins coming from cartilage explants were also found in chondrocytes supernatants. In summary, our results show differences in the labeling pattern of proteins found in supernatants from explants and monolayers. Most proteins found in the media of explants were subproducts of matrix turnover rather than newly synthesized. To our knowledge, this study is the first one so far applying SILAC technology in the context of cartilage and chondrocytes physiology.

Proteomics in asthma

Proteomic approaches have already been successfully implemented in areas such as cancer research. Surprisingly, only a few proteomics analyses have been published reporting on the protein profiles associated with asthma. Although proteomics has its limitations and experimental challenges, it can successfully contribute to the understanding of a complex disease such as asthma. We have reviewed the current literature that has reported the use of proteomic techniques to identify proteins that may contribute to altered lung function in asthma. Only a few of these studies have used proteomic techniques on human tissues associated with asthma, while most research has been performed with animal models of asthma. Proteomic applications have been used as a complimentary technique to verify the suspected candidate proteins involved in asthma. In addition, novel proteins have been identified as potential therapeutic targets. Future collaboration between the different scientific disciplines using proteomic studies of animal models of asthma and confirmation of these findings in human tissues will significantly contribute to the understanding of the etiology of asthma and lead to the development of new therapeutic strategies for this highly prevalent disease.

Porous polymer monolithic column with surface-bound gold nanoparticles for the capture and separation of cysteine-containing peptides

A new porous polymer monolithic capillary column modified with gold nanoparticles that enables the selective capture of cysteine-containing peptides has been developed to reduce the complexity of peptide mixtures generated in bottom-up proteomic analysis. The column is prepared from a poly(glycidyl methacrylate-co-ethylene dimethacrylate) monolith through reaction of some of its epoxide moieties with cysteamine to afford a monolith rich in surface thiol groups. In situ reduction of chloroauric acid within the column is then used to form gold nanoparticles attached to the surface of the pores of the monolith. This process preserves the excellent hydrodynamic properties of the monolithic column while providing a means to selectively retain cysteine-containing peptides from an analyte due to their high affinity for gold. Release of the retained peptides is subsequently achieved with an excess of 2-mercaptoethanol. The loading capacity determined for l-cysteine using frontal elution is 2.58 mumol/m. Since the gold-thiol link is less stable at elevated temperatures, the adsorption capacity is recovered by washing the column at 80 degrees C for 2 h. While regeneration is easy, the multiplicity of bonds between the monolithic support and the gold nanoparticles prevents their elution even under harsh conditions such as treatment with pure 2-mercaptoethanol or treatment with boiling water for 5 h. Application of the gold modified monolith in tandem with a packed C18 capillary column is demonstrated with baseline separation of a peptide mixture achieved in a two step process. The first involves retention of cysteine-containing peptides in monolith with reversed phase separation of all other peptides, while the retained peptides are released from monolith and separated in the second step.

Molecular pathways involved in loss of graft function in kidney transplant recipients

Interstitial fibrosis (IF) and tubular atrophy (TA) are integral parts of chronic allograft dysfunction and represent in the new classification a separate entity with or without the identification of a specific etiology. Loss of kidney graft function with IF/TA is one of the causes of most kidney allograft losses. Despite progress in immunosuppression, chronic allograft dysfunction remains the main clinical challenge for improving long-term graft survival. The sustained damage to the allograft does not represent a single entity but the summated effects of tissue injury from several pathogenic insults, as well as the kidney's healing response, modified by alloimmunity and immunosuppression. A major challenge in the future of kidney transplantation includes the study of chronic allograft dysfunction pathogenesis to identify early markers of disease progression, as well as potential therapeutics pathways.

Classical trajectories and RRKM modeling of collisional excitation and dissociation of benzylammonium and tert-butyl benzylammonium ions in a quadrupole-hexapole-quadrupole tandem mass spectrometer

Collision-induced dissociation of the benzylammonium and the 4-tert-butyl benzylammonium ions was studied experimentally in an electrospray ionization quadrupole-hexapole-quadrupole tandem mass spectrometer. Ion fragmentation efficiencies were determined as functions of the kinetic energy of ions and the collider gas (argon) pressure. A theoretical Monte Carlo model of ion collisional excitation, scattering, and decomposition was developed. The model includes simulation of the trajectories of the parent and the product ions flight through the hexapole collision cell, quasiclassical trajectory modeling of collisional activation and scattering of ions, and Rice-Ramsperger-Kassel-Marcus (RRKM) modeling of the parent ion decomposition. The results of modeling demonstrate a general agreement between calculations and experiment. Calculated values of ion fragmentation efficiency are sensitive to initial vibrational excitation of ions, scattering of product ions from the collision cell, and distribution of initial ion velocities orthogonal to the axis of the collision cell. Three critical parameters of the model were adjusted to reproduce the experimental data on the dissociation of the benzylammonium ion: reaction enthalpy and initial internal and translational temperatures of the ions. Subsequent application of the model to decomposition of the t-butyl benzylammonium ion required adjustment of the internal ion temperature only. Energy distribution functions obtained in modeling depend on the average numbers of collisions between the ion and the atoms of the collider gas and, in general, have non-Boltzmann shapes.

Integration of monolithic frit into the particulate capillary (IMFPC) column in shotgun proteome analysis

Capillary column plays an important role in nano-flow liquid chromatography coupled with tandem mass spectrometry for dealing with the high dynamic range and complexity of protein samples in shotgun proteome analysis. In this study, the integrated monolithic frit into the particulate capillary (IMFPC) column was prepared. By comparing the prepared IMFPC column with conventionally fritless capillary column, smaller size of packing materials could be easily packed into the capillary to achieve higher average peak capacity and proteome coverage. As the monolithic emitter was integrated onto this type of column, the void volume between packing particles and electrospray emitter was eliminated and the electrospray quality was improved. The prepared IMFPC column was applied to proteome analysis of mouse liver extracts, and it was observed that the number of identified proteins and peptides increased 14.9 and 12.9% as well as the peak capacity increased 11.6% by using IMFPC column over conventionally fritless capillary column.

Mass Spectrometry in Diagnostic Oncoproteomics

Diagnostic oncoproteomics is the application of proteomic techniques for the diagnosis of malignancies. A new mass spectrometric technology involves surface enhanced laser desorption ionization combined with time-of flight mass analysis (SELDI-TOF-MS), using special protein chips. After the description of the relevant principles of the technique, including approaches to proteomic pattern diagnostics, applications are reviewed for the diagnosis of ovarian, breast, prostate, bladder, pancreatic, and head and neck cancers, and also several other malignancies. Finally, problems and prospects of the approach are discussed.

The application of proteomics technology to thrombosis research: the identification of potential therapeutic targets in cardiovascular disease

Thrombus formation underpins the development of cardiovascular diseases, including acute coronary syndromes and ischaemic stroke. A number of well-characterised cardiovascular risk factors which contribute to the development of the majority of cardiovascular events have been identified, including dyslipidaemia, hypertension and diabetes. Individuals with type 2 diabetes mellitus (T2DM) have a 3- to 5-fold increased risk for development of cardiovascular disease (CVD). They may have a cluster of haemostatic abnormalities, including elevated levels of plasminogen activator inhibitor-1 (PAI-1) and fibrinogen, which contribute to acute thrombotic events. It is clear that additional unidentified risk factors contribute to the pathogenesis of cardiovascular events, and so the search for novel biomarkers and effectors, particularly in individuals with T2DM, remains a major challenge of cardiovascular medicine. Plasma and cellular proteins which contribute to thrombus formation have the potential to confer a pro-thrombotic state and represent a link between genotype, environment and disease phenotype. The comprehensive analysis of these proteins is now increasingly facilitated through the continued development of proteomic technologies which provide multifaceted approaches to the identification of novel biomarkers and/or effectors of thrombus formation and on which future anticoagulant and thrombolytic therapies may be based. This review provides an overview of current proteomic technologies. It focuses on the recent studies in which these technologies have been applied in the search for novel proteins that may confer increased risk of acute cardiovascular diseases and therefore that may influence disease progression and therapy.

Elucidation of the molecular mechanisms of preeclampsia using proteomic technologies

Preeclampsia, a disease of pregnancy, is a multisystem disorder associated with elevated maternal blood pressure, proteinurea, oedema, and fetal abnormalities. It is a major cause of mortality, morbidity, perinatal death, and premature delivery. Despite active research in the past decade, there is yet no definitive cure for preeclampsia. The disease has been treated symptomatically with antihypertensives, antieclamptics, bed rest, and a whole gamut of isolated therapies. In an attempt to understand the molecular basis of this disease and many other fatal diseases including cancer and heart disease, the scientific community has been turning to understanding the genome and more lately the "proteome". Proteomics enables researchers to identify all proteins expressed in a cell or organ and detect any PTM in the protein expression patterns. Deciphering the placental proteome and studying the differences in protein expression patterns in the normal as against the preeclamptic proteome might possibly in future lead to early detection and therapeutic targeting of preeclampsia.

Development of an integrated approach for evaluation of 2-D gel image analysis: Impact of multiple proteins in single spots on comparative proteomics in conventional 2-D gel/MALDI workflow

With 2-D gel mapping, it is often observed that essentially identical proteins migrate to different positions in the gel, while some seemingly well-resolved protein spots consist of multiple proteins. These observations can undermine the validity of gel-based comparative proteomic studies. Through a comparison of protein identifications using direct MALDI-TOF/TOF and LC-ESI-MS/MS analyses of 2-D gel separated proteins from cauliflower florets, we have developed an integrated approach to improve the accuracy and reliability of comparative 2-D electrophoresis. From 46 spots of interest, we identified 51 proteins by MALDI-TOF/TOF analysis and 108 proteins by LC-ESI-MS/MS. The results indicate that 75% of the analyzed spots contained multiple proteins. A comparison of hit rank for protein identifications showed that 37 out of 43 spots identified by MALDI matched the top-ranked hit from the ESI-MS/MS. By using the exponentially modified protein abundance index (emPAI) to determine the abundance of the individual component proteins for the spots containing multiple proteins, we found that the top-hit proteins from 40 out of 43 spots identified by MALDI matched the most abundant proteins determined by LC-MS/MS. Furthermore, our 2-D-GeLC-MS/MS results show that the top-hit proteins in 44 identified spots contributed on average 81% of the spots' staining intensity. This is the first quantitative measurement of the average rate of false assignment for direct MALDI analysis of 2-D gel spots using a new integrated workflow (2-D gel imaging, "2-D GeLC-MS/MS", and emPAI analysis). Here, the new approach is proposed as an alternative to traditional gel-based quantitative proteomics studies.

Classification and identification of bacteria using mass spectrometry-based proteomics

Timely classification and identification of bacteria is of vital importance in many areas of public health. Mass spectrometry-based methods provide an attractive alternative to well-established microbiologic procedures. Mass spectrometry methods can be characterized by the relatively high speed of acquiring taxonomically relevant information. Gel-free mass spectrometry proteomics techniques allow for rapid fingerprinting of bacterial proteins using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry or, for high-throughput sequencing of peptides from protease-digested cellular proteins, using mass analysis of fragments from collision-induced dissociation of peptide ions. The latter technique uses database searching of product ion mass spectra. A database contains a comprehensive list of protein sequences translated from protein-encoding open reading frames found in bacterial genomes. The results of such searches allow the assignment of experimental peptide sequences to matching theoretical bacterial proteomes. Phylogenetic profiles of sequenced peptides are then used to create a matrix of sequence-to-bacterium assignments, which are analyzed using numerical taxonomy tools. The results thereof reveal the relatedness between bacteria, and allow the taxonomic position of an investigated strain to be inferred.