Proteomic analysis of human plasma proteins by two-dimensional gel electrophoresis and by antibody arrays following depletion of high-abundance proteins

Characterization of the plasma proteome from healthy adult dogs

Introduction

Bloodwork is a widely used diagnostic tool in veterinary medicine, as diagnosis and therapeutic interventions often rely on blood biomarkers. However, biomarkers available in veterinary medicine often lack sensitivity or specificity. Mass spectrometry-based proteomics technology has been extensively used in the analysis of biological fluids. It offers excellent potential for a more comprehensive characterization of the plasma proteome in veterinary medicine.

Methods

In this study, we aimed to identify and quantify plasma proteins in a cohort of healthy dogs and compare two techniques for depleting high-abundance plasma proteins to enable the detection of lower-abundance proteins via label-free quantification liquid chromatography-mass spectrometry. We utilized surplus lithium-heparin plasma from 30 healthy dogs, subdivided into five groups of pooled plasma from 6 randomly selected individuals each. Firstly, we used a commercial kit to deplete high-abundance plasma proteins. Secondly, we employed an in-house method to remove albumin using Blue-Sepharose.

Results and discussion

Among all the samples, some of the most abundant proteins identified were apolipoprotein A and B, albumin, alpha-2-macroglobulin, fibrinogen beta chain, fibronectin, complement C3, serotransferrin, and coagulation factor V. However, neither of the depletion techniques achieved significant depletion of highly abundant proteins. Despite this limitation, we could detect and quantify many clinically relevant proteins. Determining the healthy canine proteome is a crucial first step in establishing a reference proteome for canine plasma. After enrichment, this reference proteome can later be utilized to identify protein markers associated with different diseases, thereby contributing to the diagnosis and prognosis of various pathologies.

Strategies for Characterization of Low-Abundant Intact or Truncated Low-Molecular-Weight Proteins From Human Plasma

Low-molecular-weight region (LMW, MW≤30kDa) of human serum/plasma proteins, including small intact proteins, truncated fragments of larger proteins, along with some other small components, has been associated with the ongoing physiological and pathological events, and thereby represent a treasure trove of diagnostic molecules. Great progress in the mining of novel biomarkers from this diagnostic treasure trove for disease diagnosis and health monitoring has been achieved based on serum samples from healthy individuals and patients and powerful new approaches in biochemistry and systems biology. However, cumulative evidence indicates that many potential LMW protein biomarkers might still have escaped from detection due to their low abundance, the dynamic complexity of serum/plasma, and the limited efficiency of characterization approaches. Here, we provide an overview of the current state of knowledge with respect to strategies for the characterization of low-abundant LMW proteins (small intact or truncated proteins) from human serum/plasma, involving prefractionation or enrichment methods to reduce dynamic range and mass spectrometry-based characterization of low-abundant LMW proteins.

Opportunities and challenges for the discovery and validation of proteomic biomarkers for common arthritic diseases

Osteoarthritis (OA) and rheumatoid arthritis (RA) are most prevalent among all the rheumatic diseases, and currently, there are no reliable biochemical measures for early diagnosis or for predicting who is likely to progress. Early diagnosis is important for making decisions on treatment options and for better management of patients. This narrative review highlights the first-generation biomarkers identified over the last two decades and focuses on the discovery and validation of candidate OA biomarkers from recent mass-spectrometry-based proteomic studies for diagnosis and monitoring disease outcomes in human. It discusses the challenges and opportunities for discovery of novel biomarkers and progress in the development of techniques for measuring biomarkers, and provides directions for future discovery and validation of biomarkers for OA and rheumatoid arthritis.

A normative study of the synovial fluid proteome from healthy porcine knee joints

Synovial fluid in an articulating joint contains proteins derived from the blood plasma and proteins that are produced by cells within the joint tissues, such as synovium, cartilage, ligament, and meniscus. The proteome composition of healthy synovial fluid and the cellular origins of many synovial fluid components are not fully understood. Here, we present a normative proteomics study using porcine synovial fluid. Using our optimized method, we identified 267 proteins with high confidence in healthy synovial fluid. We also evaluated mRNA expression data from tissues that can contribute to the synovial fluid proteome, including synovium, cartilage, blood, and liver, to better estimate the relative contributions from these sources to specific synovial fluid components. We identified 113 proteins in healthy synovial fluid that appear to be primarily derived from plasma transudates, 37 proteins primarily derived from synovium, and 11 proteins primarily derived from cartilage. Finally, we compared the identified synovial fluid proteome to the proteome of human plasma, and we found that the two body fluids share many similarities, underlining the detected plasma derived nature of many synovial fluid components. Knowing the synovial fluid proteome of a healthy joint will help to identify mechanisms that cause joint disease and pathways involved in disease progression.

Asymmetric proteome equalization of the skeletal muscle proteome using a combinatorial hexapeptide library

Immobilized combinatorial peptide libraries have been advocated as a strategy for equalization of the dynamic range of a typical proteome. The technology has been applied predominantly to blood plasma and other biological fluids such as urine, but has not been used extensively to address the issue of dynamic range in tissue samples. Here, we have applied the combinatorial library approach to the equalization of a tissue where there is also a dramatic asymmetry in the range of abundances of proteins; namely, the soluble fraction of skeletal muscle. We have applied QconCAT and label-free methodology to the quantification of the proteins that bind to the beads as the loading is progressively increased. Although some equalization is achieved, and the most abundant proteins no longer dominate the proteome analysis, at high protein loadings a new asymmetry of protein expression is reached, consistent with the formation of complex assembles of heat shock proteins, cytoskeletal elements and other proteins on the beads. Loading at different ionic strength values leads to capture of different subpopulations of proteins, but does not completely eliminate the bias in protein accumulation. These assemblies may impair the broader utility of combinatorial library approaches to the equalization of tissue proteomes. However, the asymmetry in equalization is manifest at either low and high ionic strength values but manipulation of the solvent conditions may extend the capacity of the method.

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.

Optimizing human synovial fluid preparation for two-dimensional gel electrophoresis

Background

Proteome analysis is frequently applied in identifying the proteins or biomarkers in knee synovial fluids (SF) that are associated with osteoarthritis and other arthritic disorders. The 2-dimensional gel electrophoresis (2-DE) is the technique of choice in these studies. Disease biomarkers usually appear in low concentrations and may be masked by high abundant proteins. Therefore, the main aim of this study was to find the most suitable sample preparation method that can optimize the expression of proteins on 2-DE gels that can be used to develop a reference proteome picture for non-osteoarthritic knee synovial fluid samples. Proteome pictures obtained from osteoarthritic knee synovial fluids can then be compared with the reference proteome pictures obtained in this study to assist us in identifying the disease biomarkers more correctly.

Results

The proteomic tool of 2-DE with immobilized pH gradients was applied in this study. A total of 12 2-DE gel images were constructed from SF samples that were free of osteoarthritis. In these samples, 3 were not treated with any sample preparation methods, 3 were treated with acetone, 3 were treated with 2-DE Clean-Up Kit, and 3 were treated with the combination of acetone and 2-D Clean-Up Kit prior to 2-DE analysis. Gel images were analyzed using the PDQuest Basic 8.0.1 Analytical software. Protein spots that were of interest were excised from the gels and sent for identification by mass spectrometry. Total SF total protein concentration was calculated to be 21.98 ± 0.86 mg/mL. The untreated SF samples were detected to have 456 ± 33 protein spots on 2-DE gel images. Acetone treated SF samples were detected to have 320 ± 28 protein spots, 2-D Clean-Up Kit treated SF samples were detected to have 413 ± 31 protein spots, and the combined treatment method of acetone and 2-D Clean-Up Kit was detected to have 278 ± 26 protein spots 2-DE gel images. SF samples treated with 2-D Clean-Up Kit revealed clearer presentation of the isoforms and increased intensities of the less abundant proteins of haptoglobin, apolipoprotein A-IV, prostaglandin-D synthase, alpha-1B-glycoprotein, and alpha-2-HS-glycoprotein on 2-DE gel images as compared with untreated SF samples and SF samples treated with acetone.

Conclusions

The acetone precipitation method and the combined treatment effect of acetone and 2-DE Clean-Up Kit are not preferred in preparing SF samples for 2-DE analysis as both protein intensities and numbers decrease significantly. On the other hand, 2-D Clean-Up Kit treated SF samples revealed clearer isoforms and higher intensities for the less abundant proteins of haptoglobin, apolipoprotein A-IV, prostaglandin-D synthase, alpha-1B-glycoprotein, and alpha-2-HS-glycoprotein on 2-DE gels. As a result, it is recommended that SF samples should be treated with protein clean up products such as 2-D Clean-Up Kit first before conducting proteomic research in searching for the relevant biomarkers associated with knee osteoarthritis.

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.

Depletion of abundant plasma proteins and limitations of plasma proteomics

Immunoaffinity depletion with antibodies to the top 7 or top 14 high-abundance plasma proteins is used to enhance detection of lower abundance proteins in both shotgun and targeted proteomic analyses. We evaluated the effects of top 7/top 14 immunodepletion on the shotgun proteomic analysis of human plasma. Our goal was to evaluate the impact of immunodepletion on detection of proteins across detectable ranges of abundance. The depletion columns afforded highly repeatable and efficient plasma protein fractionation. Relatively few nontargeted proteins were captured by the depletion columns. Analyses of unfractionated and immunodepleted plasma by peptide isoelectric focusing (IEF), followed by liquid chromatography-tandem mass spectrometry (LC-MS/MS), demonstrated enrichment of nontargeted plasma proteins by an average of 4-fold, as assessed by MS/MS spectral counting. Either top 7 or top 14 immunodepletion resulted in a 25% increase in identified proteins compared to unfractionated plasma. Although 23 low-abundance (<10 ng mL(-1)) plasma proteins were detected, they accounted for only 5-6% of total protein identifications in immunodepleted plasma. In both unfractionated and immunodepleted plasma, the 50 most abundant plasma proteins accounted for 90% of cumulative spectral counts and precursor ion intensities, leaving little capacity to sample lower abundance proteins. Untargeted proteomic analyses using current LC-MS/MS platforms-even with immunodepletion-cannot be expected to efficiently discover low-abundance, disease-specific biomarkers in plasma.

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.

Dual-color proteomic profiling of complex samples with a microarray of 810 cancer-related antibodies

Antibody microarrays have the potential to enable comprehensive proteomic analysis of small amounts of sample material. Here, protocols are presented for the production, quality assessment, and reproducible application of antibody microarrays in a two-color mode with an array of 1,800 features, representing 810 antibodies that were directed at 741 cancer-related proteins. In addition to measures of array quality, we implemented indicators for the accuracy and significance of dual-color detection. Dual-color measurements outperform a single-color approach concerning assay reproducibility and discriminative power. In the analysis of serum samples, depletion of high-abundance proteins did not improve technical assay quality. On the contrary, depletion introduced a strong bias in protein representation. In an initial study, we demonstrated the applicability of the protocols to proteins derived from urine samples. We identified differences between urine samples from pancreatic cancer patients and healthy subjects and between sexes. This study demonstrates that biomedically relevant data can be produced. As demonstrated by the thorough quality analysis, the dual-color antibody array approach proved to be competitive with other proteomic techniques and comparable in performance to transcriptional microarray analyses.

Proteomic profiling of amniotic fluid in preterm labor using two-dimensional liquid separation and mass spectrometry

OBJECTIVE

Simultaneous analysis of the protein composition of biological fluids is now possible. Such an approach can be used to identify biological markers of disease and to understand the pathophysiology of disorders that have eluded classification, diagnosis, and treatment. The purpose of this study was to analyze the differences in protein composition of the amniotic fluid of patients in preterm labor.

STUDY DESIGN

Amniotic fluid was obtained by amniocentesis from three groups of women with preterm labor and intact membranes: (1) women without intra-amniotic infection/inflammation (IAI) who delivered at term, (2) women without IAI who delivered a preterm neonate, and (3) women with IAI. Intra-amniotic infection was defined as a positive amniotic fluid culture for microorganisms. Intra-amniotic inflammation was defined as an elevated amniotic fluid interleukin (IL)-6 (> or =2.3 ng/mL). Two-dimensional (2D) chromatography was used for analysis. The first dimension separated proteins by isoelectric point, while the second, by the degree of hydrophobicity. 2D protein maps were generated using different experimental conditions (reducing agents as well as protein concentration). The maps were used to discern subsets of isoelectric point/hydrophobicity containing differentially expressed proteins. Protein identification of differentially expressed fractions was conducted with mass spectrometry. Enzyme-linked immunosorbent assays (ELISA) as well as surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS)-based on-chip antibody capture immunoassays were also used for confirmation of a specific protein that was differentially expressed.

RESULTS

(1) Amniotic fluid protein composition can be analyzed using a combination of 2D liquid chromatography and mass spectrometry for the identification of proteins differentially expressed in patients in preterm labor. (2) While total insulin-like growth factor-binding protein-1 (IGFBP-1) concentration did not change, IGFBP-1 fragments at about 13.5 kDa were present in patients with IAI. (3) Proteins that were over-expressed in group 1 included von Ebner gland protein precursor, IL-7 precursor, apolipoprotein A1, tropomyosin sk1 (TPMsk1) fragment, ribosomal protein S6 kinase alpha-3, and alpha-1-microglobulin/bikunin precursor (AMBP). (4) Proteins that were over-expressed in group 3 included fibrinopeptide B, transferrin, major histocompatibility complex (MHC) class 1 chain-related A antigen fragment, transcription elongation factor A, sex-determining region Y (SRY) box 5 protein, Down syndrome critical region 2 protein (DSCR2), and human peptide 8 (HP8). (5) One protein, retinol-binding protein, was over-expressed in women who delivered preterm, regardless of the presence of IAI.

CONCLUSIONS

A combination of techniques involving 2D chromatography, mass spectrometry, and immunoassays allows identification of proteins that are differentially regulated in the amniotic fluid of patients with preterm labor. Specifically, the amount of the IGFBP-1 fragments at approximately 13.5 kDa was found to be increased in patients with IAI, while the amount of the intact form of IGFBP-1 was decreased.

Mining the ovarian cancer ascites proteome for potential ovarian cancer biomarkers

Current ovarian cancer biomarkers are inadequate because of their relatively low diagnostic sensitivity and specificity. There is a need to discover and validate novel ovarian cancer biomarkers that are suitable for early diagnosis, monitoring, and prediction of therapeutic response. We performed an in-depth proteomics analysis of ovarian cancer ascites fluid. Size exclusion chromatography and ultrafiltration were used to remove high abundance proteins with molecular mass >/=30 kDa. After trypsin digestion, the subproteome (</=30 kDa) of ascites fluid was determined by two-dimensional liquid chromatography-tandem mass spectrometry. Filtering criteria were used to select potential ovarian cancer biomarker candidates. By combining data from different size exclusion and ultrafiltration fractionation protocols, we identified 445 proteins from the soluble ascites fraction using a two-dimensional linear ion trap mass spectrometer. Among these were 25 proteins previously identified as ovarian cancer biomarkers. After applying a set of filtering criteria to reduce the number of potential biomarker candidates, we identified 52 proteins for which further clinical validation is warranted. Our proteomics approach for discovering novel ovarian cancer biomarkers appears to be highly efficient because it was able to identify 25 known biomarkers and 52 new candidate biomarkers that warrant further validation.

Use of ProteinChip technology for identifying biomarkers of parasitic diseases: the example of porcine cysticercosis (Taenia solium)

Taenia solium cysticercosis is a significant public health problem in endemic countries. The current serodiagnostic techniques are not able to differentiate between infections with viable cysts and infections with degenerated cysts. The objectives of this study were to identify specific novel biomarkers of these different disease stages in the serum of experimentally infected pigs using ProteinChip technology (Bio-Rad) and to validate these biomarkers by analyzing serum samples from naturally infected pigs. In the experimental sample set 30 discriminating biomarkers (p<0.05) were found, 13 specific for the viable phenotype, 9 specific for the degenerated phenotype and 8 specific for the infected phenotype (either viable or degenerated cysts). Only 3 of these biomarkers were also significant in the field samples; however, the peak profiles were not consistent among the two sample sets. Five biomarkers discovered in the sera from experimentally infected pigs were identified as clusterin, lecithin-cholesterol acyltransferase, vitronectin, haptoglobin and apolipoprotein A-I.