Rat plasma proteomics: effects of abundant protein depletion on proteomic analysis

The proteomic analysis of plasma and serum samples represents a formidable challenge due to the presence of a few highly abundant proteins such as albumin and immunoglobulins. Detection of low abundance protein biomarkers requires therefore either the specific depletion of high abundance proteins with immunoaffinity columns and/or optimized protein fractionation methods based on charge, size or hydrophobicity. Here we describe the depletion of seven abundant rat plasma proteins with an immunoaffinity column with coupled antibodies directed against albumin, IgG, transferrin, IgM, haptoglobin, fibrinogen and alpha1-anti-trypsin. The IgY-R7-LC2 (Beckman Coulter) column showed high specificity for the targeted proteins and was able to efficiently remove most of the albumin, IgG and transferrin from rat plasma samples as judged by Western blot analysis. Depleted rat plasma protein samples were analyzed by SELDI-TOF MS, 2D SDS-PAGE and 2D-LC and compared to non-depleted plasma samples as well as to the abundant protein fraction that was eluted from the immunoaffinity column. Analysis of the depleted plasma protein fraction revealed improved signal to noise ratios, regardless of which proteomic method was applied. However, only a small number of new proteins were observed in the depleted protein fraction. Immunoaffinity depletion of abundant plasma proteins results in the significant dilution of the original sample which complicates subsequent analysis. Most proteomic approaches require specialized sample preparation procedures during which significant losses of less abundant proteins and potential biomarkers can occur. Even though abundant protein depletion reduces the dynamic range of the plasma proteome by about 2-3 orders of magnitude, the difference between medium-abundant and low abundant plasma proteins is still in the range of 7-8 orders of magnitude and beyond the dynamic range of current proteomic technologies. Thus, exploring the plasma proteome in greater detail remains a daunting task.     

iTRAQ experimental design for plasma biomarker discovery

There is considerable interest in using mass spectrometry for biomarker discovery in human blood plasma. We investigated aspects of experimental design for large studies that require analysis of multiple sample sets using iTRAQ reagents for sample multiplexing and quantitation. Immunodepleted plasma samples from healthy volunteers were compared to immunodepleted plasma from patients with osteoarthritis in eight separate iTRAQ experiments. Our analyses utilizing ProteinPilot software for peptide identification and quantitation showed that the methodology afforded excellent reproducibility from run to run for determining protein level ratios (coefficient of variation 11.7%), in spite of considerable quantitative variances observed between different peptides for a given protein. Peptides with high variances were associated with lower intensity iTRAQ reporter ions, while immunodepletion prior to sample analysis had a negligible affect on quantitative variance. We examined the influence of different reference samples, such as pooled samples or individual samples on calculating quantitative ratios. Our findings are discussed in the context of optimizing iTRAQ experimental design for robust plasma-based biomarker discovery.     

Evaluation of three principally different intact protein prefractionation methods for plasma biomarker discovery

The aim of this study was to evaluate three principally different top-down protein prefractionation methods for plasma: high-abundance protein depletion, size fractionation and peptide ligand affinity beads, focusing in particular on compatibility with downstream analysis, reproducibility and analytical depth. Our data clearly demonstrates the benefit of high-abundance protein depletion. However, MS/MS analysis of the proteins eluted from the high-abundance protein depletion column show that more proteins than aimed for are removed and, in addition, that the depletion efficacy varies between the different high-abundance proteins. Although a smaller number of proteins were identified per fraction using the peptide ligand affinity beads, this technique showed to be both robust and versatile. Size fractionation, as performed in this study, focusing on the low molecular weight proteome using a combination of gel filtration chromatography and molecular weight cutoff filters, showed limitations in the molecular weight cutoff precision leading detection of high molecular weight proteins and, in the case of the cutoff filters, high variability. GeLC-MS/MS analysis of the fractionation methods in combination with pathway analysis demonstrates that increased fractionation primarily leads to high proteome coverage of pathways related to biological functions of plasma, such as acute phase reaction, complement cascade and coagulation. Further, the prefractionation methods in this study induces limited effect on the proportion of tissue proteins detected, thereby highlighting the importance of extensive or targeted downstream fractionation.     

Utilizing human blood plasma for proteomic biomarker discovery

Candidate proteomic biomarker discovery from human plasma holds both incredible clinical potential as well as significant challenges. The dynamic range of proteins within plasma is known to exceed 10(10), and many potential biomarkers are likely present at lower protein abundances. At present, proteomic based MS analyses provide a dynamic range typically not exceeding approximately 10(3) in a single spectrum, and approximately 10(4)-10(6) when combined with on-line separations (e.g., reversed-phase gradient liquid chromatography), and thus are generally insufficient for low level biomarker detection directly from human plasma. This limitation is providing an impetus for the development of experimental methodologies and strategies to increase the possible number of detections within this biofluid. Discussed is the diversity of available approaches currently used by our laboratory and others to utilize human plasma as a viable medium for biomarker discovery. Various separation, depletion, enrichment, and quantitative efforts as well as recent improvements in MS capabilities have resulted in measurable improvements in the detection and identification of lower abundance proteins (by approximately 10-10(2)). Despite these improvements, further advances are needed to provide a basis for discovery of candidate biomarkers at very low levels. Continued development of depletion and enrichment techniques, coupled with improved pre-MS separations (both at the protein and peptide level) holds promise in extending the dynamic range of proteomic analysis.     

Comparison of diverse affinity based high-abundance protein depletion strategies for improved bio-marker discovery in oral fluids

Oral fluids (OF) have been suggested as a source of biomarkers for oral and systemic health, but as with other bio-fluids, the presence of high-abundance proteins interferes with the detection of lower-abundance biomarkers. Here, we compared the performance of four depletion treatments: triple depletion (TD) of amylases, albumins and immunoglobulin G; multiple depletion (MD) of amylases and a panel of 20 proteins, a combination of the two (EMD) and combinatorial peptide ligand library based depletion termed CPLL. TD, MD, EMD and CPLL removed 76%, 83%, 85% and 94% of total proteins, respectively, coupled with increased low abundance protein detection and narrowed dynamic range. 2-DE revealed that all depletion pretreatments successfully clarified areas hampered by high-abundance proteins; however, EMD and CPLL exposed the highest number of proteins. Quantitative MS of EMD samples relative to none treated samples indicated that most of downregulated proteins (>90%) were EMD target proteins. In conclusion, a multiple step EMD and CPLL depletion approaches bring about the highest number of protein detection ability and the best hampered-area clearance. As CPLL requires at least 10 fold more protein starting material, we suggest EMD pretreatment as a new detection tool in instances of low protein starting material.     

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.     

Direct tandem mass spectrometry reveals limitations in protein profiling experiments for plasma biomarker discovery

The low molecular weight plasma proteome and its biological relevance are not well defined; therefore, experiments were conducted to directly sequence and identify peptides observed in plasma and serum protein profiles. Protein fractionation, matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS) profiling, and liquid-chromatography coupled to MALDI tandem mass spectrometry (MS/MS) sequencing were used to analyze the low molecular weight proteome of heparinized plasma. Four fractionation techniques using functionally derivatized 96-well plates were used to extract peptides from plasma. Tandem TOF was successful for identifying peptides up to m/z 5500 with no prior knowledge of the sequence and was also used to verify the sequence assignments for larger ion signals. The peptides (n>250) sequenced in these profiles came from a surprisingly small number of proteins (n approximately 20), which were all common to plasma, including fibrinogen, complement components, antiproteases, and carrier proteins. The cleavage patterns were consistent with those of known plasma proteases, including initial cleavages by thrombin, plasmin and complement proteins, followed by aminopeptidase and carboxypeptidase activity. On the basis of these data, we discuss limitations in biomarker discovery in the low molecular weight plasma or serum proteome using crude fractionation coupled to MALDI-MS profiling.     

Chemical proteomics for drug discovery based on compound-immobilized affinity chromatography

Chemical proteomics is an effective approach to focused proteomics, having the potential to find specific interactors in moderate-scale comprehensive analysis. Unlike chemical genetics, chemical proteomics directly and comprehensively identifies proteins that bind specifically to candidate compounds by means of affinity chromatographic purification using the immobilized candidate, combined with mass spectrometric identification of interacting proteins. This is an effective approach for discovering unknown protein functions, identifying the molecular mechanisms of drug action, and obtaining information for optimization of lead compounds. However, immobilized-small molecule affinity chromatography always suffers from the problem of non-specific binders. Although several approaches were reported to reduce non-specific binding proteins, these are mainly focused on the use of low-binding-affinity beads or insertion of a spacer between the bead and the compound. Stable isotope labeling strategies have proven particularly advantageous for the discrimination of true interactors from many non-specific binders, including carrier proteins, such as serum albumin, and are expected to be valuable for drug discovery.     

Difference detection in LC-MS data for protein biomarker discovery

MOTIVATION: There is a pressing need for improved proteomic screening methods allowing for earlier diagnosis of disease, systematic monitoring of physiological responses and the uncovering of fundamental mechanisms of drug action. The combined platform of LC-MS (Liquid-Chromatography-Mass-Spectrometry) has shown promise in moving toward a solution in these areas. In this paper we present a technique for discovering differences in protein signal between two classes of samples of LC-MS serum proteomic data without use of tandem mass spectrometry, gels or labeling. This method works on data from a lower-precision MS instrument, the type routinely used by and available to the community at large today. We test our technique on a controlled (spike-in) but realistic (serum biomarker discovery) experiment which is therefore verifiable. We also develop a new method for helping to assess the difficulty of a given spike-in problem. Lastly, we show that the problem of class prediction, sometimes mistaken as a solution to biomarker discovery, is actually a much simpler problem. RESULTS: Using precision-recall curves with experimentally extracted ground truth, we show that (1) our technique has good performance using seven replicates from each class, (2) performance degrades with decreasing number of replicates, (3) the signal that we are teasing out is not trivially available (i.e. the differences are not so large that the task is easy). Lastly, we easily obtain perfect classification results for data in which the problem of extracting differences does not produce absolutely perfect results. This emphasizes the different nature of the two problems and also their relative difficulties. AVAILABILITY: Our data are publicly available as a benchmark for further studies of this nature at http://www.cs.toronto.edu/~jenn/LCMS     

Supermacroporous hydrophobic affinity cryogels for protein chromatography

N-Methacryloyl-l-tryptophan (MATrp) containing poly(2-hydroxyethyl methacrylate) based supermacroporous cryogel [PHEMATrp] was prepared for lysozyme purification form chicken egg white. MATrp was synthesized by reacting methacryloyl chloride with l-tryptophan methyl ester and provided hydrophobic functionality to the cryogel. PHEMATrp cryogel with 60–100 μm pore size was obtained by free radical polymerization of HEMA and MATrp having a specific surface area of 50 m²/g. PHEMATrp cryogel was characterized by swelling studies, FTIR and SEM. The equilibrium swelling ratios of the cryogels were 7.18 g H₂O/g for PHEMA and 6.99 g H₂O/g for PHEMATrp. Lysozyme adsorption experiments were investigated under different conditions in continuous system (i.e., medium pH, flow-rate, protein concentration, temperature, salt type). Lysozyme adsorption capacity of PHEMA and PHEMATrp cryogels from aqueous solutions was estimated as 2.9 and 46.8 mg/g (0.49 and 7.85 mg/mL), respectively. Lysozyme molecules were desorbed with 0.5 M ethylene glycol solution with 91% recovery. It was observed that PHEMATrp cryogel can be used without significant decrease in lysozyme adsorption capacity after five adsorption–desorption cycles. PHEMATrp cryogel was used for the purification of lysozyme from chicken egg white. Purity of lysozyme was estimated by SDS-PAGE. Possible denaturation of purified lysozyme was checked with fluorimetric measurements. Specific activity of the purified lysozyme was found as 43,140 U/mg using Micrococcus lysodeikticus as substrate.     

Semi-targeted plasma proteomics discovery workflow utilizing two-stage protein depletion and off-line LC-MALDI MS/MS

A quantitative proteomics workflow was implemented that provides extended plasma protein coverage by extensive protein depletion in combination with the sensitivity and breadth of analysis of two-dimensional LC-MS/MS shotgun analysis. Abundant proteins were depleted by a two-stage process using IgY and Supermix depletion columns in series. Samples are then extensively fractionated by two-dimensional chromatography with fractions directly deposited onto MALDI plates. Decoupling sample fractionation from mass spectrometry facilitates a targeted MS/MS precursor selection strategy that maximizes measurement of a consistent set of peptides across experiments. Multiplexed stable isotope labeling provides quantification relative to a common reference sample and ensures an identical set of peptides measured in the set of samples (set of eight) combined in a single experiment. The more extensive protein depletion provided by the addition of the Supermix column did not compromise overall reproducibility of the measurements or the ability to reliably detect changes in protein levels between samples. The implementation of this workflow is presented for a case study aimed at generating molecular signatures for prediction of first heart attack.     

Statistical considerations of optimal study design for human plasma proteomics and biomarker discovery

A mass spectrometry-based plasma biomarker discovery workflow was developed to facilitate biomarker discovery. Plasma from either healthy volunteers or patients with pancreatic cancer was 8-plex iTRAQ labeled, fractionated by 2-dimensional reversed phase chromatography and subjected to MALDI ToF/ToF mass spectrometry. Data were processed using a q-value based statistical approach to maximize protein quantification and identification. Technical (between duplicate samples) and biological variance (between and within individuals) were calculated and power analysis was thereby enabled. An a priori power analysis was carried out using samples from healthy volunteers to define sample sizes required for robust biomarker identification. The result was subsequently validated with a post hoc power analysis using a real clinical setting involving pancreatic cancer patients. This demonstrated that six samples per group (e.g., pre- vs post-treatment) may provide sufficient statistical power for most proteins with changes>2 fold. A reference standard allowed direct comparison of protein expression changes between multiple experiments. Analysis of patient plasma prior to treatment identified 29 proteins with significant changes within individual patient. Changes in Peroxiredoxin II levels were confirmed by Western blot. This q-value based statistical approach in combination with reference standard samples can be applied with confidence in the design and execution of clinical studies for predictive, prognostic, and/or pharmacodynamic biomarker discovery. The power analysis provides information required prior to study initiation.     

Evaluation of endogenous plasma peptide extraction methods for mass spectrometric biomarker discovery

Peptides have a role in the inflammatory response, tumor biology, and endocrine processes, presenting them as appealing biomarker candidates. However, peptide extraction efficacy for clinical profiling remains a pivotal technological challenge, as maximum coverage of the plasma peptidome is limited by a range of factors including the inherent complexity of human plasma and the lower concentration of peptides compared to abundant proteins. The aim of this study was to evaluate commonly employed peptide extraction methodologies in terms of total number of peptides detected and the mass range of peptides observed by MALDI. Despite showing coelution of proteins, solid-phase extraction (SPE) methods exhibited superior plasma peptide recovery than ultrafiltration, acetonitrile (ACN) precipitation, or size-exclusion chromatography methods under conditions employed in the study. Not surprisingly, in line with studies challenging the veracity of many peptide biomarker studies, the majority of identified peptides eluted from SPE methods corresponded to proteolytic truncations of the most abundant plasma proteins. The prefractionation of plasma with acetonitrile precipitation prior to SPE provided distinct ion signal profiles and is worthy of further study. In conclusion, this study favors the use of SPE in peptide extraction protocols for increased biomarker coverage and diversity from the plasma peptidome.     

Perspective: a program to improve protein biomarker discovery for cancer

Biomarkers for cancer risk, early detection, prognosis, and therapeutic response promise to revolutionize cancer management. Protein biomarkers offer tremendous potential in this regard due to their great diversity and intimate involvement in physiology. An effective program to discover protein biomarkers using existing technology will require team science, an integrated informatics platform, identification and quantitation of candidate biomarkers in disease tissue, mouse models of disease, standardized reagents for analyzing candidate biomarkers in bodily fluids, and implementation of automation. Technology improvements for better fractionation of the proteome, selection of specific biomarkers from complex mixtures, and multiplexed assay of biomarkers would greatly enhance progress.     

Weak affinity chromatography as a new approach for fragment screening in drug discovery

Fragment-based drug design (FBDD) is currently being implemented in drug discovery, creating a demand for developing efficient techniques for fragment screening. Due to the intrinsic weak or transient binding of fragments (mM–μM in dissociation constant (K_D)) to targets, methods must be sensitive enough to accurately detect and quantify an interaction. This study presents weak affinity chromatography (WAC) as an alternative tool for screening of small fragments. The technology was demonstrated by screening of a selected 23-compound fragment collection of documented binders, mostly amidines, using trypsin and thrombin as model target protease proteins. WAC was proven to be a sensitive, robust, and reproducible technique that also provides information about affinity of a fragment in the range of 1 mM–10 μM. Furthermore, it has potential for high throughput as was evidenced by analyzing mixtures in the range of 10 substances by WAC–MS. The accessibility and flexibility of the technology were shown as fragment screening can be performed on standard HPLC equipment. The technology can further be miniaturized and adapted to the requirements of affinity ranges of the fragment library. All these features of WAC make it a potential method in drug discovery for fragment screening.     

Cross species applicability of abundant protein depletion columns for ribulose-1,5-bisphosphate carboxylase/oxygenase

In plants, ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO) is an important enzyme in the Calvin cycle, catalyzing the first step of carbon fixation. Because of its critical role in photosynthesis, RuBisCO comprises 30-60% of the total protein content in green leaf tissue and represents a major protein which can interfere with determination of lower abundance proteins in plant proteomics. A potential solution to aid in the determination of low level proteins in plant proteomics are RuBisCO immunodepletion columns. Two formats, spin and LC, of Seppro IgY RuBisCO depletion columns were evaluated for cross species applicability. The spin and LC columns were found to deplete arabidopsis RuBisCO by greater than 90 and 98%, respectively, and automation could be achieved with the LC format. Canola RuBisCO was depleted to a similar extent, and there was evidence suggesting that corn and tobacco RuBisCO were also highly depleted in flow through fractions. Model proteins were spiked into samples to provide insight into the degree of non-specific binding. Finally, improved detection and identification of lower abundance proteins was demonstrated after depletion.