Albumin depletion of human plasma also removes low abundance proteins including the cytokines

The use of proteomics for efficient, accurate, and complete analysis of clinical samples poses a variety of technical challenges. The presence of higher abundance proteins in the plasma, such as albumin, may mask the detection of lower abundance proteins such as the cytokines. Methods have been proposed to deplete the sample of these higher abundance proteins to facilitate detection of those with lower abundance. In this study, a commercially available albumin depletion kit was used to determine if removal of albumin would measurably reduce detection of lower abundance cytokine proteins in human plasma. The Montage Albumin Deplete Kit (Millipore) was used to deplete albumin from LPS-stimulated whole blood from 15 normal human donors. Albumin depletion was measured using the BCG reagent and SDS-PAGE, and cytokine recovery was determined by a microassay immunoassay that measures both pro- and anti-inflammatory cytokines. Average albumin depletion from the samples was 72%. However, several cytokines were also significantly reduced when the albumin was removed from the plasma. Additionally, there was a variable reduction in cytokine recovery from a known mixture of cytokines in a minimal amount of plasma that were loaded onto the columns. These data demonstrate that there may be a non-specific loss of cytokines following albumin depletion, which may confound subsequent proteomic analysis.     

Dietary zinc depletion and repletion affects plasma proteins: an analysis of the plasma proteome

Zinc (Zn) deficiency is a problem world-wide. Current methods for assessing Zn status are limited to measuring plasma or serum Zn within populations suspected of deficiency. Despite the high prevalence of Zn deficiency in the human population there are no methods currently available for sensitively assessing Zn status among individuals. The purpose of this research was to utilize a proteomic approach using two-dimensional gel electrophoresis (2DE) and mass spectrometry to identify protein biomarkers that were sensitive to changes in dietary Zn levels in humans. Proteomic analysis was performed in human plasma samples (n = 6) obtained from healthy adult male subjects that completed a dietary Zn depletion/repletion protocol, current dietary zinc intake has a greater effect on fractional zinc absorption than does longer term zinc consumption in healthy adult men. Chung et al. (Am J Clin Nutr 87 (5):1224–1229, 2008). After a 13 day Zn acclimatization period where subjects consumed a Zn-adequate diet, the male subjects consumed a marginal Zn-depleted diet for 42 days followed by consumption of a Zn-repleted diet for 28 days. The samples at baseline, end of depletion and end of repletion were pre-fractionated through immuno-affinity columns to remove 14 highly abundant proteins, and each fraction separated by 2DE. Following staining by colloidal Coomassie blue and densitometric analysis, three proteins were identified by mass spectrometry as affected by changes in dietary Zn. Fibrin β and chain E, fragment double D were observed in the plasma protein fraction that remained bound to the immunoaffinity column. An unnamed protein that was related to immunoglobulins was observed in the immunodepleted plasma fraction. Fibrin β increased two-fold following the Zn depletion period and decreased to baseline values following the Zn repletion period; this protein may serve as a viable biomarker for Zn status in the future.     

Unseen proteome: mining below the tip of the iceberg to find low abundance and membrane proteins

Abundant and hydrophilic nonmembrane proteins with isoelectric points below pH 8 are the predominant proteins identified in most proteomics projects. In yeast, however, low-abundance proteins make up 80% of the predicted proteome, approximately 50% have pl's above pH 8 and 30% of the yeast ORFs are predicted to encode membrane proteins with at least 1 trans-membrane span. By applying highly solubilizing reagents and isoelectric fractionation to a membrane fraction of yeast we have a purified and identified 780 protein isoforms, representing 323 gene products, including 28% low abundance proteins and 49% membrane or membrane associated proteins. More importantly, considering the frequency and importance of co- and post-translational modifications, the separation of protein isoforms is essential and two-dimensional electrophoresis remains the only technique which offers sufficient resolution to address this at a proteomic level.     

A comparison of methods for the analysis of low abundance proteins in desmoid tumor cells

The desmoids are a group of rare clinically diverse, deep-seated fibrous neoplasms. The exact etiology is unknown, but several factors are considered to be positively correlated with their development and growth, i.e., genetic and hormonal factors and trauma. These tumors may be sporadic or associated with a genetic disease such as familial adenomatous polyposis (FAP). Devoid of metastatic potential, they tend to form large, infiltrative masses which, if not completely excised, recur repeatedly. Although surgery is widely accepted as the first-line treatment for extra-abdominal and abdominal wall desmoids, a proportion of cases are successfully palliated with either estrogen antagonists (tamoxifen, toremifene, and raloxifene) or nonsteroidal anti-inflammatory drugs. We describe and compare four methods for evaluating the expression of estrogen receptors alpha/beta and COX-1 and COX-2 in desmoid tumor-derived cells and tissues: immunocytochemistry, immunohistochemistry, RT-PCR, and two-color Western blot detection with the Odyssey infrared imaging system. Through this comparative analysis, Western blot with Odyssey was recognized as the best method to analyze the expression particularly of low expressed proteins in desmoid-derived cells. The use of a specific and reliable assessment method becomes fundamental in the evaluation of the presence and modulation of proteins which are important but weakly expressed in these rare tumors.     

Improvements in proteomic metrics of low abundance proteins through proteome equalization using ProteoMiner prior to MudPIT

Ideally, shotgun proteomics would facilitate the identification of an entire proteome with 100% protein sequence coverage. In reality, the large dynamic range and complexity of cellular proteomes results in oversampling of abundant proteins, while peptides from low abundance proteins are undersampled or remain undetected. We tested the proteome equalization technology, ProteoMiner, in conjunction with Multidimensional Protein Identification Technology (MudPIT) to determine how the equalization of protein dynamic range could improve shotgun proteomics methods for the analysis of cellular proteomes. Our results suggest low abundance protein identifications were improved by two mechanisms: (1) depletion of high abundance proteins freed ion trap sampling space usually occupied by high abundance peptides and (2) enrichment of low abundance proteins increased the probability of sampling their corresponding more abundant peptides. Both mechanisms also contributed to dramatic increases in the quantity of peptides identified and the quality of MS/MS spectra acquired due to increases in precursor intensity of peptides from low abundance proteins. From our large data set of identified proteins, we categorized the dominant physicochemical factors that facilitate proteome equalization with a hexapeptide library. These results illustrate that equalization of the dynamic range of the cellular proteome is a promising methodology to improve low abundance protein identification confidence, reproducibility, and sequence coverage in shotgun proteomics experiments, opening a new avenue of research for improving proteome coverage.     

The abundance of short proteins in the mammalian proteome

Short proteins play key roles in cell signalling and other processes, but their abundance in the mammalian proteome is unknown. Current catalogues of mammalian proteins exhibit an artefactual discontinuity at a length of 100 aa, so that protein abundance peaks just above this length and falls off sharply below it. To clarify the abundance of short proteins, we identify proteins in the FANTOM collection of mouse cDNAs by analysing synonymous and non-synonymous substitutions with the computer program CRITICA. This analysis confirms that there is no real discontinuity at length 100. Roughly 10% of mouse proteins are shorter than 100 aa, although the majority of these are variants of proteins longer than 100 aa. We identify many novel short proteins, including a “dark matter” subset containing ones that lack detectable homology to other known proteins. Translation assays confirm that some of these novel proteins can be translated and localised to the secretory pathway.     

LDL receptor-related protein 1 regulates the abundance of diverse cell-signaling proteins in the plasma membrane proteome

LDL receptor-related protein 1 (LRP1) is an endocytic receptor, reported to regulate the abundance of other receptors in the plasma membrane, including uPAR and tissue factor. The goal of this study was to identify novel plasma membrane proteins, involved in cell-signaling, that are regulated by LRP1. Membrane protein ectodomains were prepared from RAW 264.7 cells in which LRP1 was silenced and control cells using protease K. Peptides were identified by LC-MS/MS. By analysis of spectral counts, 31 transmembrane and secreted proteins were regulated in abundance at least 2-fold when LRP1 was silenced. Validation studies confirmed that semaphorin4D (Sema4D), plexin domain-containing protein-1 (Plxdc1), and neuropilin-1 were more abundant in the membranes of LRP1 gene-silenced cells. Regulation of Plxdc1 by LRP1 was confirmed in CHO cells, as a second model system. Plxdc1 coimmunoprecipitated with LRP1 from extracts of RAW 264.7 cells and mouse liver. Although Sema4D did not coimmunoprecipitate with LRP1, the cell-surface level of Sema4D was increased by RAP, which binds to LRP1 and inhibits binding of other ligands. These studies identify Plxdc1, Sema4D, and neuropilin-1 as novel LRP1-regulated cell-signaling proteins. Overall, LRP1 emerges as a generalized regulator of the plasma membrane proteome.     

Protein and peptide fractionation, enrichment and depletion: tools for the complex proteome

The identification, quantitation and global characterisation of all proteins within a given proteome are extremely challenging. This is due to the absolute detection limits of technology as well as the dynamic range in expression of proteins; and the extreme diversity and heterogeneity of the proteome. To overcome such issues, the use of separation technologies has played a critical role in reducing sample complexity. To date, a plethora of chromatographic and electrophoretic fractionation tools have evolved over the years assisting in simplifying complex protein and peptide mixtures. Here, we review a range of these technologies highlighting the challenges of protein and peptide analysis in the context of proteome research and some of the advantages and disadvantages of present techniques.     

Mycobacterial proteome extraction: comparison of disruption methods

Mycobacterium avium subsp. paratuberculosis has long been recognized as the causative agent of Johne's disease, a chronic inflammatory intestinal disease of sheep, cattle and other ruminants. Mycobacterial cells are extremely hardy, and proteomic analyses require the use of harsh conditions to effect their disruption. We compared the effectiveness of bead beating and sonication as cell lysis methods for the extraction of the proteomes of Mycobacterium avium subsp. avium and Mycobacterium avium subsp. paratuberculosis. Broad and narrow range two-dimensional gel electrophoresis was used to compare the numbers of silver stained protein spots that were observed in mycobacterial lysates. Despite differences in the yield of total protein from either species, and at different ages, the two methods appeared to give similar representations of the mycobacterial proteomes analyzed. Bead beating therefore represents a rapid and effective method of extracting the proteomes of mycobacterial species without the risks associated with an open tube sonication procedure.     

Affinity enrichment for mass spectrometry: improving the yield of low abundance biomarkers

Introduction: Mass spectrometry (MS) is the premier tool for discovering novel disease-associated protein biomarkers. Unfortunately, when applied to complex body fluid samples, MS has poor sensitivity for the detection of low abundance biomarkers (?10 ng/mL), derived directly from the diseased tissue cells or pathogens.

Areas covered: Herein we discuss the strengths and drawbacks of technologies used to concentrate low abundance analytes in body fluids, with the aim to improve the effective sensitivity for MS discovery. Solvent removal by dry-down or dialysis, and immune-depletion of high abundance serum or plasma proteins, is shown to have disadvantages compared to positive selection of the candidate biomarkers by affinity enrichment. A theoretical analysis of affinity enrichment reveals that the yield for low abundance biomarkers is a direct function of the binding affinity (Association/Dissociation rates) used for biomarker capture. In addition, a high affinity capture pre processing step can effectively dissociate the candidate biomarker from partitioning with high abundance proteins such as albumin.

Expert commentary: Properly designed high affinity capture materials can enrich the yield of low abundance (0.1–10 picograms/mL) candidate biomarkers for MS detection. Affinity capture and concentration, as an upfront step in sample preparation for MS, combined with MS advances in software and hardware that improve the resolution of the chromatographic separation can yield a transformative new class of low abundance biomarkers predicting disease risk or disease latency.     

Strategies for the enrichment and identification of basic proteins in proteome projects

Two-dimensional gel electrophoresis (2-DE) is currently the method of choice for separating complex mixtures of proteins for visual comparison in proteome analysis. This technology, however, is biased against certain classes of proteins including low abundance and hydrophobic proteins. Proteins with extremely alkaline isoelectric points (pI) are often very poorly represented using 2-DE technology, even when complex mixtures are separated using commercially available pH 6-11 or pH 7-10 immobilized pH gradients. The genome of the human gut pathogen, Helicobacter pylori, is dominated by genes encoding basic proteins, and is therefore a useful model for examining methodology suitable for separating such proteins. H. pylori proteins were separated on pH 6-11 and novel pH 9-12 immobilized pH gradients and 65 protein spots were subjected to matrix-assisted laser desorption/ionization-time of flight mass spectrometry, leading to the identification of 49 unique proteins. No proteins were characterized with a theoretical pI of greater than 10.23. A second approach to examine extremely alkaline proteins (pI > 9.0) utilized a prefractionation isoelectric focusing. Proteins were separated into two fractions using Gradiflow technology, and the extremely basic fraction subjected to both sodium dodecyl sulphate-polyacrylamide gel electrophoresis and liquid chromatography (LC) - tandem mass spectrometry post-tryptic digest, allowing the identification of 17 and 13 proteins, respectively. Gradiflow separations were highly specific for proteins with pI > 9.0, however, a single LC separation only allowed the identification of peptides from highly abundant proteins. These methods and those encompassing multiple LC 'dimensions' may be a useful complement to 2-DE for 'near-to-total' proteome coverage in the alkaline pH range.     

High sensitivity of Lobelia dortmanna to sediment oxygen depletion following organic enrichment

? Lobelia dortmanna thrives in oligotrophic, softwater lakes thanks to O(2) and CO(2) exchange across roots and uptake of sediment nutrients. We hypothesize that low gas permeability of leaves constrains Lobelia to pristine habitats because plants go anoxic in the dark if O(2) vanishes from sediments. ? We added organic matter to sediments and followed O(2) dynamics in plants and sediments using microelectrodes. To investigate plant stress, nutrient content and photosynthetic capacity of leaves were measured. ? Small additions of organic matter triggered O(2) depletion and accumulation of NH(4)(+), Fe(2+) and CO(2) in sediments. O(2) in leaf lacunae fluctuated from above air saturation in the light to anoxia late in the dark in natural sediments, but organic enrichment prolonged anoxia because of higher O(2) consumption and restricted uptake from the water. Leaf N and P dropped below minimum thresholds for cell function in enriched sediments and was accompanied by critically low chlorophyll and photosynthesis. ? We propose that anoxic stress restricts ATP formation and constrains transfer of nutrients to leaves. Brief anoxia in sediments and leaf lacunae late at night is a recurring summer phenomenon in Lobelia populations, but increased input of organic matter prolongs anoxia and reduces survival.     

Mining the plasma proteome for disease applications across seven logs of protein abundance

The current state of proteomics technologies has sufficiently advanced to allow in-depth quantitative analysis of the plasma proteome and development of a related knowledge base. Here we review approaches that have been applied to increase depth of analysis by mass spectrometry given the substantial complexity of plasma and the vast dynamic range of protein abundance. Fractionation strategies resulting in reduced complexity of individual fractions followed by mass spectrometry analysis of digests from individual fractions has allowed well in excess of 1000 proteins to be identified and quantified with high confidence that span more than seven logs of protein abundance. Such depth of analysis has contributed to elucidation of plasma proteome variation in health and of protein changes associated with disease states.     

High dynamic range characterization of the trauma patient plasma proteome

Although human plasma represents an attractive sample for disease biomarker discovery, the extreme complexity and large dynamic range in protein concentrations present significant challenges for characterization, candidate biomarker discovery, and validation. Herein we describe a strategy that combines immunoaffinity subtraction and subsequent chemical fractionation based on cysteinyl peptide and N-glycopeptide captures with two-dimensional LC-MS/MS to increase the dynamic range of analysis for plasma. Application of this "divide-and-conquer" strategy to trauma patient plasma significantly improved the overall dynamic range of detection and resulted in confident identification of 22,267 unique peptides from four different peptide populations (cysteinyl peptides, non-cysteinyl peptides, N-glycopeptides, and non-glycopeptides) that covered 3,654 different proteins with 1,494 proteins identified by multiple peptides. Numerous low abundance proteins were identified, exemplified by 78 "classic" cytokines and cytokine receptors and by 136 human cell differentiation molecules. Additionally a total of 2,910 different N-glycopeptides that correspond to 662 N-glycoproteins and 1,553 N-glycosylation sites were identified. A panel of the proteins identified in this study is known to be involved in inflammation and immune responses. This study established an extensive reference protein database for trauma patients that provides a foundation for future high throughput quantitative plasma proteomic studies designed to elucidate the mechanisms that underlie systemic inflammatory responses.     

Enhanced detection of low abundance human plasma proteins using a tandem IgY12-SuperMix immunoaffinity separation strategy

The enormous dynamic range of human bodily fluid proteomes poses a significant challenge for current MS-based proteomics technologies as it makes it especially difficult to detect low abundance proteins in human biofluids such as blood plasma, which is an essential aspect for successful biomarker discovery efforts. Here we present a novel tandem IgY12-SuperMix immunoaffinity separation system for enhanced detection of low abundance proteins in human plasma. The tandem IgY12-SuperMix system separates approximately 60 abundant proteins from the low abundance proteins in plasma, allowing for significant enrichment of low abundance plasma proteins in the SuperMix flow-through fraction. High reproducibility of the tandem separations was observed in terms of both sample processing recovery and LC-MS/MS identification results based on spectral count data. The ability to quantitatively measure differential protein abundances following application of the tandem separations was demonstrated by spiking six non-human standard proteins at three different levels into plasma. A side-by-side comparison between the SuperMix flow-through and IgY12 flow-through samples analyzed by both one- and two-dimensional LC-MS/MS revealed a 60-80% increase in proteome coverage as a result of the SuperMix separations, suggesting significantly enhanced detection of low abundance proteins. A total of 695 plasma proteins were confidently identified in a single analysis (with a minimum of two peptides per protein) by coupling the tandem separation strategy with two-dimensional LC-MS/MS, including 42 proteins with reported normal concentrations of approximately 100 pg/ml to 100 ng/ml. The concentrations of two selected proteins, macrophage colony-stimulating factor 1 and matrix metalloproteinase-8, were independently validated by ELISA as 202 pg/ml and 12.4 ng/ml, respectively. Evaluation of binding efficiency revealed that 45 medium abundance proteins were efficiently captured by the SuperMix column with >90% retention. Taken together, these results illustrate the potential broad utilities of this tandem IgY12-SuperMix strategy for proteomics applications involving human biofluids where effectively addressing the dynamic range challenge of the specimen is imperative.     

A comparison of the bovine uterine and plasma proteome using iTRAQ proteomics

Early embryo loss is a key factor affecting fertility in dairy and beef herds. Prior to implantation, the bovine embryo spends around 16 days free-floating in the uterine environment and is dependent on the composition of uterine fluid for normal growth and development. However, there is a lack of information regarding the protein composition of the bovine uterus and how it relates to plasma. In this study, uterine flushings (UF) (n = 6) and blood plasma (n = 4) were collected from beef heifers on day 7 of the oestrous cycle, albumin depleted and compared using iTRAQ proteomics. A total of 35 proteins were higher and 18 were lower in UF including metabolic enzymes, proteins with anti-oxidant activity and those involved in modulation of the immune response. This study confirms the dynamic nature of the bovine uterine proteome and that it differs from plasma. Factors affecting the uterine proteome and how it impacts on embryo survival warrant further study.     

Estimating abundance and population trends when detection is low and highly variable: A comparison of three methods for the Hermann's tortoise

Assessing population trends is a basic prerequisite to carrying out adequate conservation strategies. Selecting an appropriate method to monitor animal populations can be challenging, particularly for low-detection species such as reptiles. This study compares 3 detection-corrected abundance methods (capture–recapture, distance sampling, and N-mixture) used to assess population size of the threatened Hermann's tortoise. We used a single dataset of 432 adult tortoise observations collected at 118 sampling sites in the Plaine des Maures, southeastern France. We also used a dataset of 520 tortoise observations based on radiotelemetry data collected from 10 adult females to estimate and model the availability (g0) needed for distance sampling. We evaluated bias for N-mixture and capture–recapture, by using simulations based on different values of detection probabilities. Finally, we conducted a power analysis to estimate the ability of the 3 methods to detect changes in Hermann's tortoise abundances. The abundance estimations we obtained using distance sampling and N-mixture models were respectively 1.75 and 2.19 times less than those obtained using the capture–recapture method. Our results indicated that g0 was influenced by temperature variations and can differ for the same temperature on different days. Simulations showed that the N-mixture models provide unstable estimations for species with detection probabilities <0.5, whereas capture–recapture estimations were unbiased. Power analysis showed that none of the 3 methods were precise enough to detect slow population changes. We recommend that great care should be taken when implementing monitoring designs for species with large variation in activity rates and low detection probabilities. Although N-mixture models are easy to implement, we would not recommend using them in situations where the detection probability is very low at the risk of providing biased estimates. Among the 3 methods allowing estimation of tortoise abundances, capture–recapture should be preferred to assess population trends. © 2013 The Wildlife Society.