Comparison of different depletion strategies for improved resolution in proteomic analysis of human serum samples

Prefractionation of cerebrospinal fluid to enhance glycoprotein concentration prior to structural determination with FT-ICR mass spectrometry

Glycoproteins in cerebrospinal fluid are found to be altered in Alzheimer patients compared to healthy control individuals. We have utilized micro-solution isoelectric focusing and affinity chromatography, prior to gel electrophoresis to enable site-specific structural determination of the N-linked glycans in apolipoprotein J with the use of FT-ICR MS. The albumin depletion method is the most suitable as prefractionation method of CSF prior to 2-DE for structural determination of glycoproteins in the study of neurodegenerative disorders.

Protein depletion from blood plasma using a volatile buffer

Removal of high abundance proteins is widely used in sample processing for proteomics studies of blood plasma. Immunoaffinity (IA) depletion is currently the most specific method for performing this step. Historically, IA depletion matrices have been designed to be used with inorganic buffers. However, the presence of salts in depleted samples presents a particular problem, and these must be removed in order to make samples compatible with post-depletion processing. Desalting (dialysis, ultrafiltration, size-exclusion, etc.) usually diminishes sample integrity due to labware associated losses. Moreover, these steps require additional labor, increasing the processing time and cost of analysis. In order to avoid these problems, we have developed an IA method using a volatile buffer that can be removed from depleted samples by lyophilization. This method allows the execution of reproducible and efficient depletion of blood plasma in a semi-automated manner.

Characterization of proteins in human pancreatic cancer serum using differential gel electrophoresis and tandem mass spectrometry

The purpose of this study was to develop techniques for identifying cancer biomarkers in human serum using differential in-gel electrophoresis (DIGE), and characterizing the protein biomarkers using tandem mass spectrometry (MS/MS). A major problem in profiling protein expression by DIGE comes from the presence of high concentrations of a small number of proteins. Therefore, serum samples were first chromatographed using an immunoaffinity HPLC column (Agilent Technologies), to selectively remove albumin, immunoglobulins, transferrin, haptoglobin, and antitrypsin. Serum samples from three individuals with pancreatic cancer and three individuals without cancer were compared. Serum samples were processed using the immunoaffinity column. Differential protein analysis was performed using DIGE. A total of 56 protein spot-features were found to be significantly increased and 43 significantly decreased in cancer serum samples. These spot features were excised, trypsin digested, and analyzed by MALDI/TOF/TOF (4700 Proteomics Analyzer, Applied Biosystems). We identified 24 unique proteins that were increased and 17 unique proteins that were decreased in cancer serum samples. Western blot analysis confirmed increased levels of several of these proteins in the pancreatic cancer serum samples. In an independent series of serum samples from 20 patients with pancreatic cancer and 14 controls, increased levels of apolipoprotein E, alpha-1-antichymotrypsin, and inter-alpha-trypsin inhibitor were found to be associated with pancreatic cancer. These results suggest that affinity column enrichment and 2-D DIGE can be used to identify numerous proteins differentially expressed in serum from individuals with pancreatic cancer.

One-Step Fractionation of Complex Proteomes Enables Detection of Low Abundant Analytes Using Antibody-Based Microarrays

Antibody-based microarray is a novel technology with great promise within high-throughput proteomics. The tremendous complexity of all proteomes will, however, pose major technological challenges, especially when targeting low-abundant analytes that remains to be resolved. In this paper, we have shown that antibody microarrays readily could be used for screening of low-abundant low molecular weight analytes in complex proteomes by optimizing the sample format. Focused antibody microarrays, based on human recombinant single-chain Fv anti-cytokine antibodies on Ni2+-NTA functionalized glass slides or black polymer Maxisorp substrates, and crude cell supernatants from activated dendritic cells, containing low levels of secreted cytokines, was used for evaluation. The proteome was pre-fractionated based on size in a simple one-step procedure using centrifugal filter devices of various molecular weight cutoffs. The results showed that the generation of a nondiluted low molecular weight (LMW) fraction, corresponding to less than 2% of the original protein content, was critical for the successful screening of cytokines in the sub pg/mL range. The reduced complexity of the LMW fraction significantly improved the assay sensitivity, by improving the fluorescent tagging step and/or reducing the nonspecific binding to the substrates.

Practical proteomic biomarker discovery: taking a step back to leap forward

There is a pressing need for radically improved proteomic screening methods that allow for earlier diagnosis of disease, for systematic monitoring of physiological responses and for uncovering the fundamental mechanisms of drug action. Recent developments in proteomic technology offer tremendous, yet untapped, potential to yield novel biomarkers that are translatable to routine clinical use. Despite the significant conceptual promise of comparative proteomic profiling as a research platform for biomarker discovery, however, major hurdles remain for practical and clinical implementation. In particular, there is growing recognition that rigorous experimental design principles are urgently required to validate conclusively the unproven methodologies currently being touted. Debate and confusion persist about where the burden of proof lies: statistically, biologically or clinically? Moreover, there is no consensus about what constitutes a meaningful benchmark. An important question is how to achieve a scientifically rigorous, and therefore convincing, proof-of-concept that can be accepted by the field. Key analytical challenges related to these issues that must be addressed by the burgeoning biomarker community are discussed here.

Strategy to Design Improved Proteomic Experiments Based on Statistical Analyses of the Chemical Properties of Identified Peptides

Proteomics is an emerging field that uses many types of proteomic platforms however has few standardized procedures. Deciding which platform to use to perform large-scale proteomic studies is either based on personal preference or on so-called "figures of merit" such as dynamic range, resolution, and the limit of detection; these factors are often insufficient to predict the outcome of the experiment as the detection of peptides correlates to the chemical properties of each peptide. There is a need for a novel figure of merit that describes the overall performance of a platform based on measured output, which in proteomics is often a list of identified peptides. We report the development of such a figure of merit based on a predictive genetic algorithm. This algorithm takes into account the properties of the observed peptides such as length, hydrophobicity, and pI. Several large-scale studies that differed in sample type or platform were used to demonstrate the usefulness of the algorithm for improved experimental design. The figures that were obtained were clustered to find platforms that were biased in similar ways. Even though some platforms are different, they lead to the identification of similar peptide types and are thus redundant. The algorithm can thus be used as an exploratory tool to suggest a minimal number of complementary experiments in order to maximize experimental efficiency.

Differences among techniques for high-abundant protein depletion

The need to identify protein or peptide biomarkers via readily available biological samples like serum, plasma, or cerebrospinal fluid is often hindered by a few particular proteins present at relatively high concentrations. The ability to remove these proteins specifically, reproducibly, and with high selectivity is increasingly important in proteomic studies, and success in this procedure is leading to an ever-increasing list of lower abundant proteins being identified in these biological fluids. The current work addresses some of the potential problems in depleting proteins in typical biomarker studies, including nonspecific binding during depletion procedures and whether low molecular weight (LMW) species bind to the column in a so-called "sponge" effect caused by the ability of albumin or other high-abundant proteins to bind peptides or protein fragments. LC-MS/MS methods were applied to the comparative analysis of an IgG-based immunodepletion method and a Cibacron blue (CB)-dye-based method, for specificity of removing targeted proteins (binding fraction), as well as for assessing efficiency of target removal. This analysis was extended to examine the effects of repeated use of materials (cycles of binding and elution), in order to assess potential for carryover of one sample to the next. Capacity studies and efficiency of protein removal from the serum samples were followed for the IgG-based system using both immunochemical assays (ELISA) as well as LC-MS/MS methods. Additionally, the IgG-based system was further characterized for the removal of LMW polypeptides by nonspecific binding. We conclude that the IgG-based system provided effective removal of targeted proteins, with minimal carryover, high longevity, and minimal nonspecific binding. Significant differences are noted between the depletion techniques employed, and this should be considered based on the expectations set during experimental design.

Recent advances in blood-related proteomics

Blood is divided in two compartments, namely, plasma and cells. The latter contain red blood cells, leukocytes, and platelets. From a descriptive medical discipline, hematology has evolved towards a pioneering discipline where molecular biology has permitted the development of prognostic and diagnostic indicators for disease. The recent advance in MS and protein separation now allows similar progress in the analysis of proteins. Proteomics offers great promise for the study of proteins in plasma/serum, indeed a number of proteomics databases for plasma/serum have been established. This is a very complex body fluid containing lipids, carbohydrates, amino acids, vitamins, nucleic acids, hormones, and proteins. About 1500 different proteins have recently been identified, and a number of potential new markers of diseases have been characterized. Here, examples of the enormous promise of plasma/serum proteomic analysis for diagnostic/prognostic markers and information on disease mechanism are given. Within the blood are also a large number of different blood cell types that potentially hold similar information. Proteomics of red blood cells, until now, has not improved our knowledge of these cells, in contrast to the major progresses achieved while studying platelets and leukocytes. In the future, proteomics will change several aspects of hematology.

A novel strategy using MASCOT Distiller for analysis of cleavable isotope-coded affinity tag data to quantify protein changes in plasma

A novel strategy consisting of cleavable Isotope-Coded Affinity Tag (cICAT) combined with MASCOT Distiller was evaluated as a tool for the quantification of proteins in "abnormal" patient plasma, prepared by pooling samples from patients with acute stroke. Quantification of all light and heavy cICAT-labelled peptide ion pairs was obtained using MASCOT Distiller combined with a proprietary software. Peptides displaying differences were selected for identification by MS. These preliminary results show the promise of our approach to identify potential biomarkers.

Reversed-Phase High-Performance Liquid Chromatographic Prefractionation of Immunodepleted Human Serum Proteins to Enhance Mass Spectrometry Identification of Lower-Abundant Proteins

Serum analysis represents an extreme challenge due to the dynamic range of the proteins of interest, and the high structural complexity of the constituent proteins. In serum, the quantities of proteins and peptides of interest range from those considered "high abundance", present at 2-70% by mass of total protein, to those considered "low abundance", present at 10(-12) M or less. This range of analytical target molecules is outside the realm of available technologies for proteomic analysis. Therefore, in this study, we have developed a workflow toward addressing the complexity of these samples through the application of multidimensional separation techniques. The use of reversed-phase methods for the separation and fractionation of protein samples has been investigated, with the goal of developing an optimized serum separation for application to proteomic analysis. Samples of human serum were depleted of the six most abundant proteins, using an immunoaffinity LC method, then were separated under a variety of reversed-phase (RP) conditions using a macroporous silica C18 surface modified column material. To compare the qualities of the RP separations of this complex protein sample, absorbance chromatograms were compared, and fractions were collected for off-line SDS-PAGE and 2D-LC-MS/MS analysis. The column fractions were further investigated by determination of protein identities using either whole selected fractions, or gel bands excised from SDS-PAGE gels of the fractions. In either case samples underwent tryptic fragmentation and peptide analysis using MALDI-MS or LC-MS/MS. The preferred conditions for RP protein separation exhibited reproducibly high resolution and high protein recoveries (>98%, as determined by protein assay). Using the preferred conditions also permitted high column mass load, with up to 500 microg of protein well tolerated using a 4.6 mm ID x 50 mm column, or up to 1.5 mg on a 9.4 mm ID x 50 mm column. Elevated column temperature (80 degrees C) was observed to be a critical operational parameter, with poorer results observed at lower temperatures. The combination of sample simplification by immunoaffinity depletion combined with a robust and high recovery RP-HPLC fractionation yields samples permitting higher quality protein identifications by coupled LC-MS methods.

Reduction of the concentration difference of proteins in biological liquids using a library of combinatorial ligands

The discovery of polypeptides and proteins with relevance to a particular biological state is complicated by their vast number and concentration range in most biological mixtures. Depletion methodologies are frequently used to remove the most abundant species; however, this removal not only fails significantly to enrich trace proteins, it may also nonspecifically deplete them due to their interactions with the removed high-abundance proteins. Here we report a simple-to-use methodology that reduces the protein concentration range of a complex mixture like whole serum through the simultaneous dilution of high-abundance proteins and the concentration of low-abundance proteins. This methodology utilizes solid-phase ligand libraries of immense diversity, generated by "split, couple, recombine" combinatorial chemistry, that are used for affinity-based binding to the proteins of a given mixture. With a controlled sample-to-ligand ratio it is possible to modulate the relative concentration of proteins such that many peptides or proteins that are undetectable by classical analytical methods become easily accessible. The reduction in the dynamic range of unfractionated serum is specifically described along with treatment of other proteomes such as extracts from Escherichia coli, chicken egg white and cell culture supernatant. Mono- and bi-dimensional electrophoresis (1-DE and 2-DE respectively) and surface-enhanced laser desorption/ionization-mass spectrometry (SELDI-TOF-MS) technology demonstrate the reduction in protein concentration range. Combining this approach with additional fractionation methods further increased the number of detectable species.

A proteomic study of the apolipoproteins in LDL subclasses in patients with the metabolic syndrome and type 2 diabetes

The exchangeable apolipoproteins present in small, dense LDL (sdLDL) and large, buoyant LDL subclasses were evaluated with a quantitative proteomic approach in patients with the metabolic syndrome and with type 2 diabetes, both with subclinical atherosclerosis and the B LDL phenotype. The analyses included surface-enhanced laser adsorption/ionization, time-of-flight mass spectrometry, and subsequent identification by mass spectrometry or immunoblotting and were carried out in LDL subclasses isolated by ultracentrifugation in deuterium oxide gradients with near physiological salt concentrations. The sdLDLs of both types of patients were enriched in apolipoprotein C-III (apoC-III) and were depleted of apoC-I, apoA-I, and apoE compared with matched healthy controls with the A phenotype. The LDL complexes formed in serum from patients with diabetes with the arterial proteoglycan (PG) versican were also enriched in apoC-III. In addition, there was a significant correlation between the apoC-III content in sdLDL in patients and the apparent affinity of their LDLs for arterial versican. The unique distribution of exchangeable apolipoproteins in the sdLDLs of the patients studied, especially high apoC-III, coupled with the augmented affinity with arterial PGs, may contribute to the strong association of the dyslipidemia of insulin resistance with increased risk for cardiovascular disease.

Enrichment of low-abundant serum proteins by albumin/immunoglobulin G immunoaffinity depletion under partly denaturing conditions

We present a simple protocol for affinity depletion to remove the two most abundant serum proteins, albumin and immunoglobulin G (IgG). Under native conditions, albumin/IgG were efficiently removed and several proteins were enriched as shown by two-dimensional electrophoresis (2-DE). Besides that, partly denaturing conditions were established by adding 5 or 20% acetonitrile (ACN) in order to disrupt the binding of low-molecular-weight (LMW) proteins to the carrier proteins albumin/IgG. 2-DE results showed that the total number of detected LMW proteins increased under denaturing conditions when compared to native conditions. Interestingly, the presence of 5% ACN in serum revealed better enrichment of LMW proteins when compared to 20% ACN condition. Seven randomly distributed spots in albumin/IgG depleted serum samples under 5% ACN condition were picked from the 2-DE gels and identified by mass spectrometry (MS). The intensity of five LMW protein spots increased under denaturing conditions when compared to native conditions. Three of the seven identified spots (serum amyloid P, vitamin D-binding protein, and transthyretin) belong to a group of relatively low-abundant proteins, which make up only 1% of all serum proteins. The method presented here improves the resolution of the serum proteome by increasing the number of visualized spots on 2-D gels and allowing the detection and MS identification of LMW proteins and proteins of lower abundance.