Quantitative assessment of human serum high-abundance protein depletion

Integrative proteomic and metabolomic elucidation of cardiomyopathy with in vivo and in vitro models and clinical samples

Cardiomyopathy is a prevalent cardiovascular disease that affects individuals of all ages and can lead to life-threatening heart failure. Despite its variety in types, each with distinct characteristics and causes, our understanding of cardiomyopathy at a systematic biology level remains incomplete. Mass spectrometry-based techniques have emerged as powerful tools, providing a comprehensive view of the molecular landscape and aiding in the discovery of biomarkers and elucidation of mechanisms. This review highlights the significant potential of integrating proteomic and metabolomic approaches with specialized databases to identify biomarkers and therapeutic targets across different types of cardiomyopathies. In vivo and in vitro models, such as genetically modified mice, patient-derived or induced pluripotent stem cells, and organ chips, are invaluable in exploring the pathophysiological complexities of this disease. By integrating omics approaches with these sophisticated modeling systems, our comprehension of the molecular underpinnings of cardiomyopathy can be greatly enhanced, facilitating the development of diagnostic markers and therapeutic strategies. Among the promising therapeutic targets are those involved in extracellular matrix remodeling, sarcomere damage, and metabolic remodeling. These targets hold the potential to advance precision therapy in cardiomyopathy, offering hope for more effective treatments tailored to the specific molecular profiles of patients.

Effects of filtration and alpha-amylase depletion on salivary biochemical composition measurements

The effects of filtration (F) and alpha-amylase depletion (AD) were assessed in n = 34 saliva samples. Each saliva sample was split into three aliquots and treated as follows: (1) no treatment; (2) 0.45μm commercial filter; and (3) 0.45μm commercial filter and affinity depletion of alpha-amylase. Then, a panel of biochemical biomarkers consisting of amylase, lipase, alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma-glutamyl transferase (GGT), alkaline phosphatase (ALP), creatine kinase (CK), calcium, phosphorus, total protein, albumin, urea, creatinine, cholesterol, triglycerides, and uric acid was measured. Differences between the different aliquots were observed in all measured analytes. The most marked changes were found in triglycerides and lipase data for filtered samples, and in alpha-amylase, uric acid, triglycerides, creatinine, and calcium results in alpha-amylase-depleted aliquots. In conclusion, the salivary filtration and amylase depletion methods employed in this report caused significant changes in saliva composition measurements. Based on these results, it would be recommended to consider the possible effects of these treatments in salivary biomarkers when filtration or amylase depletion is performed.

Isobaric Labeling Strategy Utilizing 4-Plex N,N-Dimethyl Leucine (DiLeu) Tags Reveals Proteomic Changes Induced by Chemotherapy in Cerebrospinal Fluid of Children with B-Cell Acute Lymphoblastic Leukemia

The use of mass spectrometry for protein identification and quantification in cerebrospinal fluid (CSF) is at the forefront of research efforts to identify and explore biomarkers for the early diagnosis and prognosis of neurologic disorders. Here we implemented a 4-plex N,N-dimethyl leucine (DiLeu) isobaric labeling strategy in a longitudinal study aiming to investigate protein dynamics in children with B-cell acute lymphoblastic leukemia (B-cell ALL) undergoing chemotherapy. The temporal profile of CSF proteome during chemotherapy treatment at weeks 5, 10-14, and 24-28 highlighted many differentially expressed proteins, such as neural cell adhesion molecule, neuronal growth regulator 1, and secretogranin-3, all of which play important roles in neurodegenerative diseases. A total of 63 proteins were significantly altered across all of the time points investigated. The most over-represented biological processes from gene ontology analysis included platelet degranulation, complement activation, cell adhesion, fibrinolysis, neuron projection, regeneration, and regulation of neuron death. We expect that results from this and future studies will provide a means to monitor neurotoxicity and develop strategies to prevent central nervous system injury in response to chemotherapy in children.

Characterization of Cerebrospinal Fluid via Data-Independent Acquisition Mass Spectrometry

Cerebrospinal fluid (CSF) is in direct contact with the brain and serves as a valuable specimen to examine diseases of the central nervous system through analyzing its components. These include the analysis of metabolites, cells as well as proteins. For identifying new suitable diagnostic protein biomarkers bottom-up data-dependent acquisition (DDA) mass spectrometry-based approaches are most popular. Drawbacks of this method are stochastic and irreproducible precursor ion selection. Recently, data-independent acquisition (DIA) emerged as an alternative method. It overcomes several limitations of DDA, since it combines the benefits of DDA and targeted methods like selected reaction monitoring (SRM). We established a DIA method for in-depth proteome analysis of CSF. For this, four spectral libraries were generated with samples from native CSF ( n = 5), CSF fractionation (15 in total) and substantia nigra fractionation (54 in total) and applied to three CSF DIA replicates. The DDA and DIA methods for CSF were conducted with the same nanoLC parameters using a 180 min gradient. Compared to a conventional DDA method, our DIA approach increased the number of identified protein groups from 648 identifications in DDA to 1574 in DIA using a comprehensive spectral library generated with DDA measurements from five native CSF and 54 substantia nigra fractions. We also could show that a sample specific spectral library generated from native CSF only increased the identification reproducibility from three DIA replicates to 90% (77% with a DDA method). Moreover, by utilizing a substantia nigra specific spectral library for CSF DIA, over 60 brain-originated proteins could be identified compared to only 11 with DDA. In conclusion, the here presented optimized DIA method substantially outperforms DDA and could develop into a powerful tool for biomarker discovery in CSF. Data are available via ProteomeXchange with the identifiers PXD010698, PXD010708, PXD010690, PXD010705, and PXD009624.

Fluorescamine Labeling for Assessment of Protein Conformational Change and Binding Affinity in Protein-Nanoparticle Interaction

Protein adsorption alters the "biological identity" of nanoparticles (NPs) and could affect how biosystems respond to invading NPs. Study of protein-NP interaction can help understand how the physicochemical properties of NPs impact the interaction and thus potentially guide the design of safer and more effective NPs for biomedical or other applications. Binding affinity between proteins and NPs and the occurrence of protein conformational change upon binding to NPs are two important aspects to be learned, but few methods are currently available to assess both simultaneously in a simple way. Herein, we demonstrated that the fluorescamine labeling method developed by our group not only could reveal protein conformational change upon adsorption to NPs, owing to its capability to label the primary amines exposed on protein surface, but also could be applied to measure the binding affinity. By screening the interaction between a large number of proteins and four types of NPs, the present study also revealed that protein adsorption onto NPs could be strongly affected by structure flexibility. The proteins with high structure flexibility experienced high degrees of conformation change when binding to the polystyrene NPs, which could potentially influence protein function. Overall, we demonstrate that our assay is a quick, simple, and high-throughput tool to reveal potential impacts on protein activity and evaluate the strength of protein-NP binding.

A Routine 'Top-Down' Approach to Analysis of the Human Serum Proteome

Serum provides a rich source of potential biomarker proteoforms. One of the major obstacles in analysing serum proteomes is detecting lower abundance proteins owing to the presence of hyper-abundant species (e.g., serum albumin and immunoglobulins). Although depletion methods have been used to address this, these can lead to the concomitant removal of non-targeted protein species, and thus raise issues of specificity, reproducibility, and the capacity for meaningful quantitative analyses. Altering the native stoichiometry of the proteome components may thus yield a more complex series of issues than dealing directly with the inherent complexity of the sample. Hence, here we targeted method refinements so as to ensure optimum resolution of serum proteomes via a top down two-dimensional gel electrophoresis (2DE) approach that enables the routine assessment of proteoforms and is fully compatible with subsequent mass spectrometric analyses. Testing included various fractionation and non-fractionation approaches. The data show that resolving 500 µg protein on 17 cm 3–10 non-linear immobilised pH gradient strips in the first dimension followed by second dimension resolution on 7–20% gradient gels with a combination of lithium dodecyl sulfate (LDS) and sodium dodecyl sulfate (SDS) detergents markedly improves the resolution and detection of proteoforms in serum. In addition, well established third dimension electrophoretic separations in combination with deep imaging further contributed to the best available resolution, detection, and thus quantitative top-down analysis of serum proteomes.

Extracellular Protein Phosphorylation, the Neglected Side of the Modification

The very existence of extracellular phosphorylation has been questioned for a long time, although casein phosphorylation was discovered a century ago. In addition, several modification sites localized on secreted proteins or on extracellular or lumenal domains of transmembrane proteins have been catalogued in large scale phosphorylation analyses, though in most such studies this aspect of cellular localization was not considered. Our review presents examples when additional analyses were performed on already public data sets that revealed a wealth of information about this "neglected side" of the modification. We also sum up accumulated knowledge about extracellular phosphorylation, including the discovery of Golgi-residing kinases and the special difficulties encountered in targeted analyses. We hope future phosphorylation studies will not ignore the existence of phosphorylation outside of the cell, and further discoveries will shed more light on its biological role.

Contributions of immunoaffinity chromatography to deep proteome profiling of human biofluids

Human biofluids, especially blood plasma or serum, hold great potential as the sources of candidate biomarkers for various diseases; however, the enormous dynamic range of protein concentrations in biofluids represents a significant analytical challenge for detecting promising low-abundance proteins. Over the last decade, various immunoaffinity chromatographic methods have been developed and routinely applied for separating low-abundance proteins from the high- and moderate-abundance proteins, thus enabling much more effective detection of low-abundance proteins. Herein, we review the advances of immunoaffinity separation methods and their contributions to the proteomic applications in human biofluids. The limitations and future perspectives of immunoaffinity separation methods are also discussed.

Comparison of Depletion Strategies for the Enrichment of Low-Abundance Proteins in Urine

Proteome analysis of complex biological samples for biomarker identification remains challenging, among others due to the extended range of protein concentrations. High-abundance proteins like albumin or IgG of plasma and urine, may interfere with the detection of potential disease biomarkers. Currently, several options are available for the depletion of abundant proteins in plasma. However, the applicability of these methods in urine has not been thoroughly investigated. In this study, we compared different, commercially available immunodepletion and ion-exchange based approaches on urine samples from both healthy subjects and CKD patients, for their reproducibility and efficiency in protein depletion. A starting urine volume of 500 μL was used to simulate conditions of a multi-institutional biomarker discovery study. All depletion approaches showed satisfactory reproducibility (n=5) in protein identification as well as protein abundance. Comparison of the depletion efficiency between the unfractionated and fractionated samples and the different depletion strategies, showed efficient depletion in all cases, with the exception of the ion-exchange kit. The depletion efficiency was found slightly higher in normal than in CKD samples and normal samples yielded more protein identifications than CKD samples when using both initial as well as corresponding depleted fractions. Along these lines, decrease in the amount of albumin and other targets as applicable, following depletion, was observed. Nevertheless, these depletion strategies did not yield a higher number of identifications in neither the urine from normal nor CKD patients. Collectively, when analyzing urine in the context of CKD biomarker identification, no added value of depletion strategies can be observed and analysis of unfractionated starting urine appears to be preferable.

Deeper insight into chronic kidney disease-related atherosclerosis: comparative proteomic studies of blood plasma using 2DE and mass spectrometry

Background

Atherosclerosis is a major cause of cardiac events and mortality in patients suffering from chronic kidney disease (CKD). Moreover, the risk of cardiovascular disease (CVD) development in patients with CKD increases as kidney function declines. Although the close connection between atherosclerosis and kidney dysfunction is undeniable, particular risk factors and specific mechanisms that promote CVD in patients with CKD remain unclear. To gain insight into better recognition of the mechanisms of accelerated atherosclerosis in patients with CKD, we performed a comparative proteomic analysis of blood plasma from patients in various stages of CKD and thus distinct progression of atherosclerosis (n = 90), patients with advanced CVD and normal renal function (n = 30) and healthy volunteers (n = 30).

Methods

Plasma samples were depleted using affinity chromatography and divided into three fractions: high-abundant, low-abundant and low-molecular weight proteins. The first two fractions were analyzed by two-dimensional gel electrophoresis and mass spectrometry, the last one has been subjected to direct MS/MS analysis. A proteomic profiles for high-abundant, low-abundant and low-molecular weight proteins fractions were obtained. Differential accumulated proteins were confirmed by selected reaction monitoring analysis (SRM). The Gene Ontology (GO) function and the interaction networks of differentially expressed proteins were then analyzed.

Results

Forty-nine proteins (13 high- and 36 low-molecular mass) showed differences in accumulation levels. For eleven of them differential expression were confirmed by selected reaction monitoring analysis. Bioinformatic analysis showed that identified differential proteins were related to three different processes: the blood coagulation cascade, the transport, binding and metabolism of lipoproteins and inflammatory processes.

Conclusions

Obtained data provide an additional line of evidence that different molecular mechanisms are involved in the development of CKD- and CVD-related atherosclerosis. The abundance of some anti-atherogenic factors revealed in patients with CKD suggests that these factors are not associated with the reduction of atherosclerosis progression in CKD that is typically observed in “classical” CVD. Moreover, obtained data also suggest that mechanism of CVD acceleration may be different in initial and advanced stages of CKD. Undoubtedly, in advanced stages of CKD inflammation is highly pronounced.

Electronic supplementary material

The online version of this article (doi:10.1186/s12967-014-0378-8) contains supplementary material, which is available to authorized users.

Optimization of plasma sample pretreatment for quantitative analysis using iTRAQ labeling and LC-MALDI-TOF/TOF

Shotgun proteomic methods involving iTRAQ (isobaric tags for relative and absolute quantitation) peptide labeling facilitate quantitative analyses of proteomes and searches for useful biomarkers. However, the plasma proteome's complexity and the highly dynamic plasma protein concentration range limit the ability of conventional approaches to analyze and identify a large number of proteins, including useful biomarkers. The goal of this paper is to elucidate the best approach for plasma sample pretreatment for MS- and iTRAQ-based analyses. Here, we systematically compared four approaches, which include centrifugal ultrafiltration, SCX chromatography with fractionation, affinity depletion, and plasma without fractionation, to reduce plasma sample complexity. We generated an optimized protocol for quantitative protein analysis using iTRAQ reagents and an UltrafleXtreme (Bruker Daltonics) MALDI TOF/TOF mass spectrometer. Moreover, we used a simple, rapid, efficient, but inexpensive sample pretreatment technique that generated an optimal opportunity for biomarker discovery. We discuss the results from the four sample pretreatment approaches and conclude that SCX chromatography without affinity depletion is the best plasma sample preparation pretreatment method for proteome analysis. Using this technique, we identified 1,780 unique proteins, including 1,427 that were quantified by iTRAQ with high reproducibility and accuracy.

Preparation of the low molecular weight serum proteome for mass spectrometry analysis

The discovery of viable biomarkers or indicators of disease states is complicated by the inherent complexity of the chosen biological specimen. Every sample, whether it is serum, plasma, urine, tissue, cells, or a host of others, contains thousands of large and small components, each interacting in multiple ways. The need to concentrate on a group of these components to narrow the focus on a potential biomarker candidate becomes, out of necessity, a priority, especially in the search for immune-related low molecular weight serum biomarkers. One such method in the field of proteomics is to divide the sample proteome into groups based on the size of the protein, analyze each group, and mine the data for statistically significant items. This chapter details a portion of this method, concentrating on a method for fractionating and analyzing the low molecular weight proteome of human serum.

Top-down proteomics: enhancing 2D gel electrophoresis from tissue processing to high-sensitivity protein detection

The large-scale resolution and detection of proteins from complex native mixtures is fundamental to quantitative proteomic analyses. Comprehensive analyses depend on careful tissue handling and quantitative protein extraction and assessment. To most effectively link these analyses with an understanding of underlying molecular mechanisms, it is critical that all protein types - isoforms, splice variants and those with functionally important PTMs - are quantitatively extracted with high reproducibility. Methodological details concerning protein extraction and resolution using 2DE are discussed with reference to current in-gel protein detection limits. We confirm a significant increase in total protein, and establish that extraction, resolution and detection of phospho- and glycoproteins are improved following automated frozen disruption relative to manual homogenisation. The quality of 2DE protein resolution is established using third-dimension separations and 'deep imaging'; substantially more proteins/protein species than previously realised are actually resolved by 2DE. Thus, the key issue for effective proteome analyses is most likely to be detection, not resolution. Thus, these systematic methodological and technical advances further solidify the role of 2DE in top-down proteomics. By routinely assessing as much proteomic data from a sample as possible, 2DE enables more detailed and critical insights into molecular mechanisms underlying different physiological states.

Proteomic sample preparation for blast wound characterization

Background

Blast wounds often involve diverse tissue types and require substantial time and treatment for appropriate healing. Some of these subsequent wounds become colonized with bacteria requiring a better understanding of how the host responds to these bacteria and what proteomic factors contribute wound healing outcome. In addition, using reliable and effective proteomic sample preparation procedures can lead to novel biomarkers for improved diagnosis and therapy.

Results

To address this need, suitable sample preparation for 2-D DIGE proteomic characterization of wound effluent and serum samples from combat-wounded patients was investigated. Initial evaluation of crude effluent and serum proved the necessity of high abundant protein depletion. Subsequently, both samples were successfully depleted using Agilent Multiple Affinity Removal system and showed greatly improved 2-D spot maps, comprising 1,800 and 1,200 protein spots, respectively.

Conclusion

High abundant protein removal was necessary for both wound effluent and serum. This is the first study to show a successful method for high abundant protein depletion from wound effluent which is compatible with downstream 2-D DIGE analysis. This development allows for improved biomarker discovery in wound effluent and serum samples.

Performance evaluation of affinity ligands for depletion of abundant plasma proteins

Human plasma is a commonly used diagnostic fluid in clinical chemistry. In-depth plasma proteomic analysis is performed to search for disease biomarkers, however the large dynamic range of protein abundance in plasma presents a substantial analytical challenge. Removal of abundant plasma proteins using antibody capture approaches is a common and attractive means to reduce sample complexity and to aid the analysis of lower abundance proteins of interest. A novel class of heavy chain camelid-derived affinity ligands produced in Saccharomyces cerevisiae, has recently been developed as an alternative to antibody-based depletion methods. Here, we evaluate the performance characteristics of these ligands for removal of high abundance plasma proteins. Affinity ligands were tested for the removal of 14 abundant human plasma proteins. The performance characteristics were evaluated by gel-electrophoresis and LC-MS/MS of the bound and flow-through fractions. The capacity of a 5.6mL column was found to be 125μL of plasma. Replicate analysis demonstrated high column reproducibility and linearity, efficient removal of abundant proteins, and enrichment of lower abundance proteins observed after depletion. The novel class of affinity ligands provides an attractive alternative to traditional antibody-based immunodepletion methods.

Ultradepletion of human plasma using chicken antibodies: a proof of concept study

Human plasma arguably represents the most comprehensive version of the human proteome. Despite its immense theoretical discovery potential, plasma has many high and medium abundance proteins that mask low abundance protein disease biomarkers of relevance, making the discovery of novel diagnostic markers particularly difficult. Some form of protein depletion and/or fractionation is essential in order to detect markers of low abundance. Here, we describe a "proof of concept" two-pronged approach to immunodeplete abundant proteins from human plasma. The method, called API (Abundant Protein Immunodepletion), involves the fractionation of plasma using dual ion exchange columns (protein repetitive orthogonal offline fractionation (PROOF)) to simplify the proteome, the production of polyclonal IgY against each fraction and finally using the purified antibodies in a immunodepletion column. We explored the use of this product for immunodepletion of human plasma and identified a total of 165 nonredundant proteins after depletion. Of these, 38 proteins that were not previously identified in nondepleted plasma were now detected. It is envisaged that further optimization of the method as well as its cyclic implementation (by reinjecting depleted plasma into chickens for second round of antibody production) can make this technology highly robust, extremely cost-effective, and ideal for high throughput biomarker discovery.

Avian IgY antibodies and their recombinant equivalents in research, diagnostics and therapy

The generation and use of avian antibodies is of increasing interest in a wide variety of applications within the life sciences. Due to their phylogenetic distance, mechanisms of immune diversification and the way in which they deposit IgY immunoglobulin in the egg yolk, chickens provide a number of advantages compared to mammals as hosts for immunization. These advantages include: the one-step purification of antibodies from egg yolk in large amounts facilitates having a virtually continuous supply; the epitope spectrum of avian antibodies potentially grants access to novel specificities; the broad absence of cross-reactivity with mammalian epitopes avoids assay interference and improves the performance of immunological techniques. The polyclonal nature of IgY antibodies has limited their use since avian hybridoma techniques are not well established. Recombinant IgY, however, can be generated from mammalian monoclonal antibodies which makes it possible to further exploit the advantageous properties of the IgY scaffold. Moreover, cloning and selecting the immune repertoire from avian organisms is highly efficient, yielding antigen-specific antibody fragments. The recombinant approach is well suited to circumvent any limitations of polyclonal antibodies. This review presents comprehensive information on the generation, purification, modification and applications of polyclonal and monoclonal IgY antibodies.

DIGE proteome analysis reveals suitability of ischemic cardiac in vitro model for studying cellular response to acute ischemia and regeneration

Proteomic analysis of myocardial tissue from patient population is suited to yield insights into cellular and molecular mechanisms taking place in cardiovascular diseases. However, it has been limited by small sized biopsies and complicated by high variances between patients. Therefore, there is a high demand for suitable model systems with the capability to simulate ischemic and cardiotoxic effects in vitro, under defined conditions. In this context, we established an in vitro ischemia/reperfusion cardiac disease model based on the contractile HL-1 cell line. To identify pathways involved in the cellular alterations induced by ischemia and thereby defining disease-specific biomarkers and potential target structures for new drug candidates we used fluorescence 2D-difference gel electrophoresis. By comparing spot density changes in ischemic and reperfusion samples we detected several protein spots that were differentially abundant. Using MALDI-TOF/TOF-MS and ESI-MS the proteins were identified and subsequently grouped by functionality. Most prominent were changes in apoptosis signalling, cell structure and energy-metabolism. Alterations were confirmed by analysis of human biopsies from patients with ischemic cardiomyopathy.With the establishment of our in vitro disease model for ischemia injury target identification via proteomic research becomes independent from rare human material and will create new possibilities in cardiac research.

Circulating biomarkers of protein oxidation for Alzheimer disease: expectations within limits

Alzheimer disease (AD), the most common dementing disorder, is a multifactorial disease with complex etiology. Among different hypotheses proposed for AD one of the most corroborated is the "oxidative stress hypothesis". Although recent studies extensively demonstrated the specific oxidative modification of selected proteins in the brain of AD patients and how their dysfunction possibly correlates with the pathology, there is still an urgent need to extend these findings to peripheral tissue. So far very few studies showed oxidative damage of proteins in peripheral tissues and current findings need to be replicated. Another limit in AD research is represented by the lack of highly specific diagnostic tools for early diagnosis. For a full screening and early diagnosis, biomarkers easily detectable in biological samples, such as blood, are needed. The search of reliable biomarkers for AD in peripheral blood is a great challenge. A few studies described a set of plasma markers that differentiated AD from controls and were shown to be useful in predicting conversion from mild cognitive impairment, which is considered a prodromal stage, to AD. We review the current state of knowledge on peripheral oxidative biomarkers for AD, including proteomics, which might be useful for early diagnosis and prognosis.

Pitfalls in protein quantitation using acid-catalyzed O18 labeling: hydrolysis-driven deamidation

Proteolysis combined with O(18) labeling emerged recently as a powerful tool for quantitation of proteins for which suitable internal standards cannot be produced using molecular biology methods. Several recent reports suggested that acid-catalyzed O(18) labeling may be superior to the commonly accepted enzymatic protocol, as it may allow more significant spacing between the isotopic clusters of labeled and unlabeled peptides, thereby eliminating signal interference and enhancing the quality of quantitation. However, careful examination of this procedure reveals that the results of protein quantitation assisted by acid-catalyzed O(18) labeling are highly peptide-dependent. The inconsistency was found to be caused by deamidation of Asn, Gln, and carbamidomethylated Cys residues during prolonged exposure of the proteolytic fragments to the acidic environment of the labeling reaction, which translates into a loss in signal for these peptides. Taking deamidation into account leads to a significant improvement in the consistency of quantitation across a range of different proteolytic fragments.

A systematic analysis of eluted fraction of plasma post immunoaffinity depletion: implications in biomarker discovery

Plasma is the most easily accessible source for biomarker discovery in clinical proteomics. However, identifying potential biomarkers from plasma is a challenge given the large dynamic range of proteins. The potential biomarkers in plasma are generally present at very low abundance levels and hence identification of these low abundance proteins necessitates the depletion of highly abundant proteins. Sample pre-fractionation using immuno-depletion of high abundance proteins using multi-affinity removal system (MARS) has been a popular method to deplete multiple high abundance proteins. However, depletion of these abundant proteins can result in concomitant removal of low abundant proteins. Although there are some reports suggesting the removal of non-targeted proteins, the predominant view is that number of such proteins is small. In this study, we identified proteins that are removed along with the targeted high abundant proteins. Three plasma samples were depleted using each of the three MARS (Hu-6, Hu-14 and Proteoprep 20) cartridges. The affinity bound fractions were subjected to gelC-MS using an LTQ-Orbitrap instrument. Using four database search algorithms including MassWiz (developed in house), we selected the peptides identified at <1% FDR. Peptides identified by at least two algorithms were selected for protein identification. After this rigorous bioinformatics analysis, we identified 101 proteins with high confidence. Thus, we believe that for biomarker discovery and proper quantitation of proteins, it might be better to study both bound and depleted fractions from any MARS depleted plasma sample.

Mass spectrometry of peptides and proteins from human blood

It is difficult to convey the accelerating rate and growing importance of mass spectrometry applications to human blood proteins and peptides. Mass spectrometry can rapidly detect and identify the ionizable peptides from the proteins in a simple mixture and reveal many of their post-translational modifications. However, blood is a complex mixture that may contain many proteins first expressed in cells and tissues. The complete analysis of blood proteins is a daunting task that will rely on a wide range of disciplines from physics, chemistry, biochemistry, genetics, electromagnetic instrumentation, mathematics and computation. Therefore the comprehensive discovery and analysis of blood proteins will rank among the great technical challenges and require the cumulative sum of many of mankind's scientific achievements together. A variety of methods have been used to fractionate, analyze and identify proteins from blood, each yielding a small piece of the whole and throwing the great size of the task into sharp relief. The approaches attempted to date clearly indicate that enumerating the proteins and peptides of blood can be accomplished. There is no doubt that the mass spectrometry of blood will be crucial to the discovery and analysis of proteins, enzyme activities, and post-translational processes that underlay the mechanisms of disease. At present both discovery and quantification of proteins from blood are commonly reaching sensitivities of ∼1 ng/mL.

Putative biomarkers and targets of estrogen receptor negative human breast cancer

Breast cancer is a progressive and potentially fatal disease that affects women of all ages. Like all progressive diseases, early and reliable diagnosis is the key for successful treatment and annihilation. Biomarkers serve as indicators of pathological, physiological, or pharmacological processes. Her2/neu, CA15.3, estrogen receptor (ER), progesterone receptor (PR), and cytokeratins are biomarkers that have been approved by the Food and Drug Administration for disease diagnosis, prognosis, and therapy selection. The structural and functional complexity of protein biomarkers and the heterogeneity of the breast cancer pathology present challenges to the scientific community. Here we review estrogen receptor-related putative breast cancer biomarkers, including those of putative breast cancer stem cells, a minor population of estrogen receptor negative tumor cells that retain the stem cell property of self-renewal. We also review a few promising cytoskeleton targets for ER alpha negative breast cancer.

A systematic analysis of the effects of increasing degrees of serum immunodepletion in terms of depth of coverage and other key aspects in top-down and bottom-up proteomic analyses

Immunodepletion of clinical fluids to overcome the dominance by a few very abundant proteins has been explored but studies are few, commonly examining only limited aspects with one analytical platform. We have systematically compared immunodepletion of 6, 14, or 20 proteins using serum from renal transplant patients, analysing reproducibility, depth of coverage, efficiency, and specificity using 2-D DIGE (‘top-down’) and LC-MS/MS (‘bottom-up’). A progressive increase in protein number (≥2 unique peptides) was found from 159 in unfractionated serum to 301 following 20 protein depletion using a relatively high-throughput 1-D-LC-MS/MS approach, including known biomarkers and moderate–lower abundance proteins such as NGAL and cytokine/growth factor receptors. On the contrary, readout by 2-D DIGE demonstrated good reproducibility of immunodepletion, but additional proteins seen tended to be isoforms of existing proteins. Depletion of 14 or 20 proteins followed by LC-MS/MS showed excellent reproducibility of proteins detected and a significant overlap between columns. Using label-free analysis, greater run-to-run variability was seen with the Prot20 column compared with the MARS14 column (median %CVs of 30.9 versus 18.2%, respectively) and a corresponding wider precision profile for the Prot20. These results illustrate the potential of immunodepletion followed by 1-D nano-LC-LTQ Orbitrap Velos analysis in a moderate through-put biomarker discovery process.

High abundance proteins depletion vs low abundance proteins enrichment: comparison of methods to reduce the plasma proteome complexity

BACKGROUND

To date, the complexity of the plasma proteome exceeds the analytical capacity of conventional approaches to isolate lower abundance proteins that may prove to be informative biomarkers. Only complex multistep separation strategies have been able to detect a substantial number of low abundance proteins (<100 ng/ml). The first step of these protocols is generally the depletion of high abundance proteins by the use of immunoaffinity columns or, alternatively, the enrichment of by the use of solid phase hexapeptides ligand libraries.

METHODOLOGY/PRINCIPAL FINDINGS

Here we present a direct comparison of these two approaches. Following either approach, the plasma sample was further fractionated by SCX chromatography and analyzed by RP-LC-MS/MS with a Q-TOF mass spectrometer. The depletion of the 20 most abundant plasma proteins allowed the identification of about 25% more proteins than those detectable following low abundance proteins enrichment. The two datasets are partially overlapping and the identified proteins belong to the same order of magnitude in terms of plasma concentration.

CONCLUSIONS/SIGNIFICANCE

Our results show that the two approaches give complementary results. However, the enrichment of low abundance proteins has the great advantage of obtaining much larger amount of material that can be used for further fractionations and analyses and emerges also as a cheaper and technically simpler approach. Collectively, these data indicate that the enrichment approach seems more suitable as the first stage of a complex multi-step fractionation protocol.

Bioinformatics challenges in the proteomic analysis of human plasma

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

Comparison of methods for depletion of albumin and IgG from equine serum

BACKGROUND

Disease-specific biomarkers hold diagnostic promise in both human and veterinary medicine, but serum biomarkers in low concentrations may be masked by the presence of abundant proteins, mostly albumin and IgG. Methods to deplete albumin and IgG exist, but efficacy of these methods for depleting equine serum of these proteins has not been established.

OBJECTIVE

The aim of this study was to determine if albumin and IgG could be depleted from equine serum using several commercially available kits and procedures.

METHODS

One-dimensional gel electrophoresis followed by densitometry was used to determine percent of albumin, IgG, and both in pooled serum from 3 horses before and after application of 7 depletion methods. Repeatability was determined by applying the 2 best methods to serum samples from 6 grade horses.

RESULTS

For pooled serum, depletion rates varied from 35-90% for albumin and 0-94% for IgG. In the repeatability study, the ProteoExtract method combined with protein G Sepharose beads to remove additional IgG provided the best overall performance with 66% albumin depletion and 100% IgG depletion. A protocol using protein G Sepharose beads to remove IgG followed by ethanol precipitation of nonalbumin proteins with albumin remaining in the supernatant was the second most effective, with 85% albumin depletion and 55% IgG depletion. Although a multiprotein immunodepletion column effectively removed 90% of the albumin, the method was ineffective at removing IgG.

CONCLUSION

Albumin and IgG removal kits optimized for human use have variable efficacy for equine serum. Combined use of the ProteoExtract kit and manual incubation with protein G Sepharose beads provided the most effective depletion.

Proteomics and the search for biomarkers of female reproductive diseases

Over the past decade, high-throughput proteomics technologies have evolved considerably and have become increasingly more commonly applied to the investigation of female reproductive diseases. Proteomic approaches facilitate the identification of new disease biomarkers by comparing the abundance of hundreds of proteins simultaneously to find those specific to a particular clinical condition. Some of the best studied areas of female reproductive biology applying proteomics include gynaecological cancers, endometriosis and endometrial infertility. This review will discuss the progress that has been made in these areas and will highlight some of the emerging technologies that promise to contribute to better understanding of the female reproductive disease.

High-abundance proteins depletion for serum proteomic analysis: concomitant removal of non-targeted proteins

In clinical and pharmaceutical proteomics, serum and plasma are frequently used for detection of early diagnostic biomarkers for therapeutic targets. Although obtaining these body fluid samples is non-invasive and easy, they contain some abundant proteins that mask other protein components present at low concentrations. The challenge in identifying serum biomarkers is to remove the abundant proteins, uncovering and enriching at the same time the low-abundance ones. The depletion strategies, however, could lead to the concomitant removal of some non-targeted proteins that may be of potential interest. In this study, we compared three different methods aimed to deplete high-abundance proteins from human serum, focusing on the identification of non-specifically bound proteins which might be eventually removed. A Cibacron blue-dye-based method for albumin removal, an albumin and IgG immunodepletion method and an immunoaffinity column (Multiple Affinity Removal System) that simultaneously removes a total of six high-abundance proteins, were investigated. The bound proteins were eluted, separated by two-dimensional gel electrophoresis and identified by Nano LC-CHIP-MS system. Flow-through fractions and bound fractions were also analysed with the ProteinChip technology SELDI-TOF-MS. Our results showed that the methods tested removed not only the targeted proteins with high efficiency, but also some non-targeted proteins. We found that the Multiple Affinity Removal Column improved the intensity of low-abundance proteins, displayed new protein spots and increased resolution. Notably, the column showed the lowest removal of untargeted proteins, proved to be the most promising depletion approach and a reliable method for serum preparation prior to proteomic studies.

High-abundance protein depletion: comparison of methods for human plasma biomarker discovery

Affinity depletion of abundant proteins from human plasma has become a routine sample preparation strategy in proteomics used prior to protein identification and quantitation. To date, there have been limited published studies comparing the performance of commercially available depletion products. We conducted a thorough evaluation of six depletion columns using 2-DE combined with sophisticated image analysis software, examining the following criteria: (i) efficiency of high-abundance protein depletion, (ii) non-specific removal of other than the targeted proteins and (iii) total number of protein spots detected on the gels following depletion. From all the products investigated, the Seppro IgY system provided the best results. It displayed the greatest number of protein spots on the depleted plasma gels, minimal non-specific binding and high efficiency of abundant protein removal. Nevertheless, the increase in the number of detected spots compared with the second best performing and cheaper multiple affinity removal column (MARC) was not shown to be statistically significant. The ProteoPrep spin column, considered to be the "deepest" depletion technique available at the time of conducting the study, surprisingly displayed significantly fewer spots on the flow-through fraction gels compared with both the Seppro and the MARC. The spin column format and low plasma capacity were also found to be impractical for 2-DE. To conclude, we succeeded in providing an overview of the depletion columns performances with regard to the three examined areas. Our study will serve as a reference to other scientists when deciding on the optimal product for their particular projects.

Immunoprecipitation on magnetic beads and liquid chromatography-tandem mass spectrometry for carbonic anhydrase II quantification in human serum

In this study, a magnetic bead-based platform amenable to high-throughput protein carbonic anhydrase II (CA II) capture is presented. The key steps in this approach involved immunoaffinity purification of the target protein from serum followed by on-bead digestion with trypsin to release a surrogate peptide. This tryptic peptide was quantified by liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS) operating in multiple reaction monitoring acquisition mode. Using a synthetic peptide standard and a structural analogue free-labeled internal standard, the resulting concentration was stoichiometrically converted to CA II serum concentration. The analytical steps, such as preparation of immunobeads, protein capture, proteolysis, and calibration, were optimized. The method was validated in terms of recovery (77%), reproducibility (relative standard deviation [RSD]<12%), and method detection limit (0.5 pmol ml(-1)). The developed method was applied to determining the CA II in eight healthy subjects, and the concentration measured was 27.3 pmol ml(-1) (RSD = 65%).

Current technological challenges in biomarker discovery and validation

In this review we will give an overview of the issues related to biomarker discovery studies with a focus on liquid chromatography-mass spectrometry (LC-MS) methods. Biomarker discovery is based on a close collaboration between clinicians, analytical scientists and chemometritians/statisticians. It is critical to define the final purpose of a biomarker or biomarker pattern at the onset of the study and to select case and control samples accordingly. This is followed by designing the experiment, starting with the sampling strategy, sample collection, storage and separation protocols, choice and validation of the quantitative profiling platform followed by data processing, statistical analysis and validation workflows. Biomarker candidates that result after statistical validation should be submitted for further validation and, ideally, be connected to the disease mechanism after their identification. Since most discovery studies work with a relatively small number of samples, it is necessary to assess the specificity and sensitivity of a given biomarker-based assay in a larger set of independent samples, preferably analyzed at another clinical center. Targeted analytical methods of higher throughput than the original discovery method are needed at this point and LC-tandem mass spectrometry is gaining acceptance in this field. Throughout this review, we will focus on possible sources of variance and how they can be assessed and reduced in order to avoid false positives and to reduce the number of false negatives in biomarker discovery research.