Affinity as a tool in life science

Immobilization of albumin binding domain (ABD) on Sepharose 4B and magnetic particle for efficient single-step purification of human serum albumin

Human serum albumin (HSA) is an important protein in plasma with various biological functions in the human body. Due to its unique features in the binding and transfer of ligands and pharmaceutical molecules, HSA is extensively used in therapeutics and pharmaceutical approaches. Commercial albumin is produced by a multi-step process of plasma fractionation. However, this traditional method has some limitations such as risk of contamination, low quality, and quantity of the purified final protein. In this study, we developed two affinity chromatography platforms for the purification of human serum albumin. The recombinant albumin-binding domain (ABD) was expressed and purified using molecular biology techniques. Two types of commercial beads-Cyanogen bromide-activated Sepharose 4B and amine-functionalized magnetic particles-were then functionalized with the recombinant ABD. Protein purification using chromatography columns demonstrated that HSA can be purified to 95 % purity in a single step. Circular dichroism (CD) spectroscopy revealed structural similarities in HSA purified through affinity chromatography and fractionation using the Cohen method. Furthermore, the study of aspirin binding to HSA demonstrated that proteins purified via affinity chromatography and those fractionated by the Cohen method exhibited identical drug-binding affinities. The results of this study may have important implications for the clinical purification of human serum albumin.

Protein purification with light via a genetically encoded azobenzene side chain

Affinity chromatography is the method of choice for the rapid purification of proteins from cell extracts or culture supernatants. Here, we present the light-responsive Azo-tag, a short peptide comprising p-(phenylazo)-L-phenylalanine (Pap), whose side chain can be switched from its trans-ground state to the metastable cis-configuration by irradiation with mild UV light. Since only trans-Pap shows strong affinity to α-cyclodextrin (α-CD), a protein exhibiting the Azo-tag selectively binds to an α-CD chromatography matrix under daylight or in the dark but elutes quickly under physiological buffer flow when illuminating the column at 355 nm. We demonstrate the light-controlled single-step purification - termed Excitography - of diverse proteins, including enzymes and antibody fragments, without necessitating competing agents or harsh buffer conditions as normally applied. While affinity chromatography has so far been governed by chemical interactions, introducing control by electromagnetic radiation as a physical principle adds another dimension to this widely applied separation technique.

Updates on Aptamer Research

For many years, different probing techniques have mainly relied on antibodies for molecular recognition. However, with the discovery of aptamers, this has changed. The science community is currently considering using aptamers in molecular targeting studies because of the many potential advantages they have over traditional antibodies. Some of these possible advantages are their specificity, higher binding affinity, better target discrimination, minimized batch-to-batch variation, and reduced side effects. Overall, these characteristics of aptamers have attracted scholars to use them as molecular probes in place of antibodies, with some aptamer-based targeting products being now available in the market. The present review is aimed at discussing the potential of aptamers as probes in molecular biology and in super-resolution microscopy.

DiffSLC: A graph centrality method to detect essential proteins of a protein-protein interaction network

Identification of central genes and proteins in biomolecular networks provides credible candidates for pathway analysis, functional analysis, and essentiality prediction. The DiffSLC centrality measure predicts central and essential genes and proteins using a protein-protein interaction network. Network centrality measures prioritize nodes and edges based on their importance to the network topology. These measures helped identify critical genes and proteins in biomolecular networks. The proposed centrality measure, DiffSLC, combines the number of interactions of a protein and the gene coexpression values of genes from which those proteins were translated, as a weighting factor to bias the identification of essential proteins in a protein interaction network. Potentially essential proteins with low node degree are promoted through eigenvector centrality. Thus, the gene coexpression values are used in conjunction with the eigenvector of the network's adjacency matrix and edge clustering coefficient to improve essentiality prediction. The outcome of this prediction is shown using three variations: (1) inclusion or exclusion of gene co-expression data, (2) impact of different coexpression measures, and (3) impact of different gene expression data sets. For a total of seven networks, DiffSLC is compared to other centrality measures using Saccharomyces cerevisiae protein interaction networks and gene expression data. Comparisons are also performed for the top ranked proteins against the known essential genes from the Saccharomyces Gene Deletion Project, which show that DiffSLC detects more essential proteins and has a higher area under the ROC curve than other compared methods. This makes DiffSLC a stronger alternative to other centrality methods for detecting essential genes using a protein-protein interaction network that obeys centrality-lethality principle. DiffSLC is implemented using the igraph package in R, and networkx package in Python. The python package can be obtained from git.io/diffslcpy. The R implementation and code to reproduce the analysis is available via git.io/diffslc.

Close Encounters - Probing Proximal Proteins in Live or Fixed Cells

The well-oiled machinery of the cellular proteome operates via variable expression, modifications, and interactions of proteins, relaying genomic and transcriptomic information to coordinate cellular functions. In recent years, a number of techniques have emerged that serve to identify sets of proteins acting in close proximity in the course of orchestrating cellular activities. These proximity-dependent assays, including BiFC, BioID, APEX, FRET, and isPLA, have opened up new avenues to examine protein interactions in live or fixed cells. We review herein the current status of proximity-dependent in situ techniques. We compare the advantages and limitations of the methods, underlining recent progress and the growing importance of these techniques in basic research, and we discuss their potential as tools for drug development and diagnostics.

DeepPPI: Boosting Prediction of Protein-Protein Interactions with Deep Neural Networks

The complex language of eukaryotic gene expression remains incompletely understood. Despite the importance suggested by many proteins variants statistically associated with human disease, nearly all such variants have unknown mechanisms, for example, protein-protein interactions (PPIs). In this study, we address this challenge using a recent machine learning advance-deep neural networks (DNNs). We aim at improving the performance of PPIs prediction and propose a method called DeepPPI (Deep neural networks for Protein-Protein Interactions prediction), which employs deep neural networks to learn effectively the representations of proteins from common protein descriptors. The experimental results indicate that DeepPPI achieves superior performance on the test data set with an Accuracy of 92.50%, Precision of 94.38%, Recall of 90.56%, Specificity of 94.49%, Matthews Correlation Coefficient of 85.08% and Area Under the Curve of 97.43%, respectively. Extensive experiments show that DeepPPI can learn useful features of proteins pairs by a layer-wise abstraction, and thus achieves better prediction performance than existing methods. The source code of our approach can be available via http://ailab.ahu.edu.cn:8087/DeepPPI/index.html .

Development of immunoaffinity chromatographic method for Ara h 2 isolation

Ara h 2 is considered a major allergen in peanut. Due to the difficulty of separation, Ara h 2 had not been fully studied. Immunoaffinity chromatography (IAC) column can separate target protein with high selectivity, which made it possible to purify Ara h 2 from different samples. In this study, IAC method was developed to purify Ara h 2 and its effect was evaluated. By coupling polyclonal antibody (pAb) on CNBr-activated Sepharose 4B, the column for specific extraction was constructed. The coupling efficiency of the IAC column was higher than 90%, which made the capacity of column reached 0.56 mg per 0.15 g medium (dry weight). The recovery of Ara h 2 ranged from 93% to 100% for different concentrations of pure Ara h 2 solutions in 15 min. After using a column 10 times, about 88% of the column capacity remained. When applied to extract Ara h 2 from raw peanut protein extract and boiled peanut protein extract, the IAC column could recovery 94% and 88% target protein from the mixture. SDS-PAGE and Western blotting analysis confirmed the purified protein was Ara h 2, its purity reached about 90%. Significantly, the IAC column could capture dimer of Ara h 2, which made it feasible to prepared derivative of protein after processing.

Detecting reliable non interacting proteins (NIPs) significantly enhancing the computational prediction of protein-protein interactions using machine learning methods

Protein-protein interactions (PPIs) play a vital role in most biological processes. Hence their comprehension can promote a better understanding of the mechanisms underlying living systems. However, besides the cost and the time limitation involved in the detection of experimentally validated PPIs, the noise in the data is still an important issue to overcome. In the last decade several in silico PPI prediction methods using both structural and genomic information were developed for this purpose. Here we introduce a unique validation approach aimed to collect reliable non interacting proteins (NIPs). Thereafter the most relevant protein/protein-pair related features were selected. Finally, the prepared dataset was used for PPI classification, leveraging the prediction capabilities of well-established machine learning methods. Our best classification procedure displayed specificity and sensitivity values of 96.33% and 98.02%, respectively, surpassing the prediction capabilities of other methods, including those trained on gold standard datasets. We showed that the PPI/NIP predictive performances can be considerably improved by focusing on data preparation.

A Highly Diverse and Functional Naïve Ubiquitin Variant Library for Generation of Intracellular Affinity Reagents

We report the design, construction, and validation of a highly diverse phage-displayed naïve ubiquitin variant (Ubv) library. We first conducted a mutation tolerance scan of 27 residues and confirmed that 24 of these could be substituted by chemically diverse amino acids without compromising the display of Ubvs on phage. Subsequently, we constructed a library containing 6.8×10¹⁰ unique members, in which these 24 positions were diversified with a degenerate codon that encodes for 6 aa that are prevalent in protein interaction sites. To ensure the optimal structural stability of the Ubvs, we constructed the library in a two-step process, whereby 12 positions were randomized first, and following the selection for displayed Ubvs, the resulting pool was further diversified at the other 12 positions. The resulting library was validated by conducting binding selections against a panel of 40 diverse protein antigens and was found to be as functional as a highly validated synthetic antibody library, yielding binders against 30 of the antigens. Detailed characterization of an Ubv that bound to the cell-surface receptor human epidermal growth factor receptor 3 revealed tight binding in the single-digit nanomolar range. Moreover, Ubvs that bound to two distinct sites on the intracellular adapter Grb2 could be combined to generate a potent inhibitor that functioned in cells. These results validate ubiquitin as a robust scaffold for the construction of naïve libraries that can be used to generate Ubvs that target signaling networks both outside and inside the cells.

Millisecond single-molecule localization microscopy combined with convolution analysis and automated image segmentation to determine protein concentrations in complexly structured, functional cells, one cell at a time

We present a single-molecule tool called the CoPro (concentration of proteins) method that uses millisecond imaging with convolution analysis, automated image segmentation and super-resolution localization microscopy to generate robust estimates for protein concentration in different compartments of single living cells, validated using realistic simulations of complex multiple compartment cell types. We demonstrate its utility experimentally on model Escherichia coli bacteria and Saccharomyces cerevisiae budding yeast cells, and use it to address the biological question of how signals are transduced in cells. Cells in all domains of life dynamically sense their environment through signal transduction mechanisms, many involving gene regulation. The glucose sensing mechanism of S. cerevisiae is a model system for studying gene regulatory signal transduction. It uses the multi-copy expression inhibitor of the GAL gene family, Mig1, to repress unwanted genes in the presence of elevated extracellular glucose concentrations. We fluorescently labelled Mig1 molecules with green fluorescent protein (GFP) via chromosomal integration at physiological expression levels in living S. cerevisiae cells, in addition to the RNA polymerase protein Nrd1 with the fluorescent protein reporter mCherry. Using CoPro we make quantitative estimates of Mig1 and Nrd1 protein concentrations in the cytoplasm and nucleus compartments on a cell-by-cell basis under physiological conditions. These estimates indicate a ∼4-fold shift towards higher values in the concentration of diffusive Mig1 in the nucleus if the external glucose concentration is raised, whereas equivalent levels in the cytoplasm shift to smaller values with a relative change an order of magnitude smaller. This compares with Nrd1 which is not involved directly in glucose sensing, and which is almost exclusively localized in the nucleus under high and low external glucose levels. CoPro facilitates time-resolved quantification of protein concentrations in single functional cells, and enables the distributions of concentrations across a cell population to be measured. This could be useful in investigating several cellular processes that are mediated by proteins, especially where changes in protein concentration in a single cell in response to changes in the extracellular chemical environment are subtle and rapid and may be smaller than the variability across a cell population.

Characterization of monoclonal antibody's binding kinetics using oblique-incidence reflectivity difference approach

Monoclonal antibodies (mAbs) against human proteins are the primary protein capture reagents for basic research, diagnosis, and molecular therapeutics. The 2 most important attributes of mAbs used in all of these applications are their specificity and avidity. While specificity of a mAb raised against a human protein can be readily defined based on its binding profile on a human proteome microarray, it has been a challenge to determine avidity values for mAbs in a high-throughput and cost-effective fashion. To undertake this challenge, we employed the oblique-incidence reflectivity difference (OIRD) platform to characterize mAbs in a protein microarray format. We first systematically determined the K_on and K_off values of 50 mAbs measured with the OIRD method and deduced the avidity values. Second, we established a multiplexed approach that simultaneously measured avidity values of a mixture of 9 mono-specific mAbs that do not cross-react to the antigens. Third, we demonstrated that avidity values of a group of mAbs could be sequentially determined using a flow-cell device. Finally, we implemented a sequential competition assay that allowed us to bin multiple mAbs that recognize the same antigens. Our study demonstrated that OIRD offers a high-throughput and cost-effective platform for characterization of the binding kinetics of mAbs.

High throughput monoclonal antibody generation by immunizing multiple antigens

Recognizing proteins via the production of highly specific monoclonal antibodies (mAbs) is crucial to identifying proteins for proteomic research. However, traditional mAb generation is time-consuming with low efficiency. In this study, we assessed the high throughput method of producing mAbs by immunizing mice with multiple antigens in order to obtain hybridomas against these multiple antigens in one cell fusion. We selected eight proteins that play important roles in human physiological or pathological processes. These proteins were mixed and simultaneously administered to one mouse. We observed the immunizing period for 10 d, and determined the effect of liquid medium and semi-solid medium in hybridoma generation. As a result, all eight immunogens induced antibodies in the immunized mouse in one cell fusion, we obtained hybridomas specific to all eight proteins by enzyme-linked immuno sorbent assay (ELISA) screening, hybridomas against five out of eight showed specific positive in Western-blotting assays. This indicates that we generated mAbs specific to eight proteins in one cell fusion, greatly increasing the efficiency of mAb generation. Furthermore, we observed that hybridomas selected from the liquid medium and semi-solid medium showed different reactivity to antigens. Our study established high-throughput and time-saving methods for production of mAbs. These results provide alternative approaches for increasing the efficacy of mAb generation.

1D4: a versatile epitope tag for the purification and characterization of expressed membrane and soluble proteins

Incorporation of short epitope tags into proteins for recognition by commercially available monoclonal or polyclonal antibodies has greatly facilitated the detection, characterization, localization, and purification of heterologously expressed proteins for structure-function studies. A number of tags have been developed, but many epitope-antibody combinations do not work effectively for all immunochemical techniques due to the nature of the tag and the specificity of the antibodies. A highly versatile, multipurpose epitope tag is the 9 amino acid C-terminal 1D4 peptide. This peptide tag together with the Rho1D4 monoclonal antibody can be used to detect proteins in complex mixtures by western blotting and ELISA assays, localize proteins in cells by immunofluorescence and immunoelectron microscopic labeling techniques, identify subunits and interacting proteins by co-immunoprecipitation, and purify functionally active proteins including membrane proteins by immunoaffinity chromatography. In this chapter we describe various immunochemical procedures which can be used for the detection, purification and localization of 1D4-tagged proteins for structure-function studies.

Purification of E. coli proteins using a self-cleaving chitin-binding affinity tag

The use of affinity tags to purify recombinant proteins is ubiquitous in molecular biology. However, tag removal after purification still remains a challenge. The most commonly used method, proteolytic digestion, has several drawbacks that make the process complex and costly. One alternative to the use of proteolytic digestion is the use of self-cleaving purification tags. Here, we describe a system that combines a chitin-binding domain (CBD) tag with the ∆I-CM intein to yield a self-cleaving purification tag. A protein gene of interest is genetically fused downstream of the tag, generating a fusion protein that can be rapidly and easily purified using a chitin resin. Intein self-cleavage is then induced by a simple pH and temperature shift, liberating the free target protein. This system can be used to readily purify any recombinant protein that can be expressed in E. coli, and has the potential to be applied to a wide variety of additional tags and expression hosts.

Combined use of irreversible binding and MRM technology for low- and ultralow copy-number protein detection and quantitation

In this paper, we present a method for the determination of low- and ultralow copy-number proteins in biomaterials based on a combination of concentrating the protein from the sample onto cyanogen bromide-activated Sepharose 4B (via nonspecific binding of free amino groups) and MRM. The detection limit and the dependence of the MRM peak areas on the concentration of protein in the sample were determined using the proteins CYP102 and BSA, as a model system, both in solution and after their addition to human plasma. Nonspecific protein enrichment of proteins from diluted sample volumes of 10-50 mL was found to increase the range of linear dependence of the chromatographic peak area on concentration by more than three orders of magnitude, allowing a lower LOD limit (LLOD) of as low as 10(-18) M. At this LLOD, at least two tryptic peptides of CYP102 and BSA could be detected with S/N of ≥7.0. The results were equally good for samples containing pure protein mixtures and proteins spiked into diluted depleted human blood plasma.

Determining proteome-wide expression levels using reverse protein arrays in fission yeast

Global protein expression profiling of various mutants or growth conditions is currently a major challenge in biology. Here we provide a protocol for a strategy that we recently developed that couples ORFeome-based (ORF denotes open reading frame) expression to reverse protein arrays; this approach accurately quantifies more than 99% of the predicted fission yeast proteins in various genetic backgrounds. The first stage of this two-stage protocol requires mass mating between any fertile fission yeast mutant of interest and the integrated fission yeast-tagged ORFeome followed by selection of recombinant haploids. The second stage of the protocol, called reverse protein arrays, involves simple large-scale extraction of total proteins, which are then spotted on nitrocellulose membranes for detection by quantitative dot blot. When handled manually, the entire protocol takes about 2 months. However, the process could easily be automated and should also be applicable to other organisms.

Rapid identification of monospecific monoclonal antibodies using a human proteome microarray

To broaden the range of tools available for proteomic research, we generated a library of 16,368 unique full-length human ORFs that are expressible as N-terminal GST-His₆ fusion proteins. Following expression in yeast, these proteins were then individually purified and used to construct a human proteome microarray. To demonstrate the usefulness of this reagent, we developed a streamlined strategy for the production of monospecific monoclonal antibodies that used immunization with live human cells and microarray-based analysis of antibody specificity as its central components. We showed that microarray-based analysis of antibody specificity can be performed efficiently using a two-dimensional pooling strategy. We also demonstrated that our immunization and selection strategies result in a large fraction of monospecific monoclonal antibodies that are both immunoblot and immunoprecipitation grade. Our data indicate that the pipeline provides a robust platform for the generation of monoclonal antibodies of exceptional specificity.

Simultaneous purification and site-specific modification of pyrroline-carboxy-lysine proteins

Sticky residue: Pyrroline-carboxy-lysine (Pcl) can be readily incorporated into proteins expressed in E. coli and mammalian cells by using the pyrrolysyl tRNA/tRNA synthetase pair. Pcl can be used as a single amino acid purification tag and can be site-specifically modified with functional probes during the elution process.

Estimation of absolute protein quantities of unlabeled samples by selected reaction monitoring mass spectrometry

For many research questions in modern molecular and systems biology, information about absolute protein quantities is imperative. This information includes, for example, kinetic modeling of processes, protein turnover determinations, stoichiometric investigations of protein complexes, or quantitative comparisons of different proteins within one sample or across samples. To date, the vast majority of proteomic studies are limited to providing relative quantitative comparisons of protein levels between limited numbers of samples. Here we describe and demonstrate the utility of a targeting MS technique for the estimation of absolute protein abundance in unlabeled and nonfractionated cell lysates. The method is based on selected reaction monitoring (SRM) mass spectrometry and the “best flyer” hypothesis, which assumes that the specific MS signal intensity of the most intense tryptic peptides per protein is approximately constant throughout a whole proteome. SRM-targeted best flyer peptides were selected for each protein from the peptide precursor ion signal intensities from directed MS data. The most intense transitions per peptide were selected from full MS/MS scans of crude synthetic analogs. We used Monte Carlo cross-validation to systematically investigate the accuracy of the technique as a function of the number of measured best flyer peptides and the number of SRM transitions per peptide. We found that a linear model based on the two most intense transitions of the three best flying peptides per proteins (TopPep3/TopTra2) generated optimal results with a cross-correlated mean fold error of 1.8 and a squared Pearson coefficient R² of 0.88. Applying the optimized model to lysates of the microbe Leptospira interrogans, we detected significant protein abundance changes of 39 target proteins upon antibiotic treatment, which correlate well with literature values. The described method is generally applicable and exploits the inherent performance advantages of SRM, such as high sensitivity, selectivity, reproducibility, and dynamic range, and estimates absolute protein concentrations of selected proteins at minimized costs.

Classification of protein profiles from antibody microarrays using heat and detergent treatment

Antibody microarrays offer new opportunities for exploring the proteome and to identify biomarker candidates in human serum and plasma. Here, we have investigated the effect of heat and detergents on an antibody-based suspension bead array (SBA) assay using polyclonal antibodies and biotinylated plasma samples. With protein profiles from more than 2300 antibodies generated in 384-plex antibody SBAs, three major classes of heat and detergent susceptibility could be described. The results show that washing of the beads with SDS (rather than Tween) after target binding lowered intensity levels of basically all profiles and that about 50% of the profiles appeared to be lowered to a similar extent by heating of the sample. About 33% of the profiles appeared to be insensitive to heat treatment while another 17% showed a positive influence of heat to yield elevated profiles. The results suggest that the classification of antibodies is driven by the molecular properties of the antibody-antigen interaction and can generally not be predicted based on protein class or Western blot data. The experimental scheme presented here can be used to systematically categorize antibodies and thereby combine antibodies with similar properties into targeted arrays for analysis of plasma and serum.

Divide and conquer: the application of organelle proteomics to heart failure

Chronic heart failure is a worldwide cause of mortality and morbidity and is the final outcome of a number of different etiologies. This reflects both the complexity of the disease and our incomplete understanding of its underlying molecular mechanisms. One experimental approach to address this is to study subcellular organelles and how their functions are activated and synchronized under physiological and pathological conditions. In this review, we discuss the application of proteomic technologies to organelles and how this has deepened our perception of the cellular proteome and its alterations with heart failure. The use of proteomics to monitor protein quantity and posttranslational modifications has revealed a highly intricate and sophisticated level of protein regulation. Posttranslational modifications have the potential to regulate organelle function and interplay most likely by targeting both structural and signaling proteins throughout the cell, ultimately coordinating their responses. The potentials and limitations of existing proteomic technologies are also discussed emphasizing that the development of novel methods will enhance our ability to further investigate organelles and decode intracellular communication.

High-Throughput Antibody Generation Using Multiplexed Immunization and Immunogen Array Analysis

In this work, the authors developed a new screening approach using multiplexed immunization and immunogen array analysis to improve the efficiency of antibody screening for high-throughput antibody generation. The immunogen array is based on a 96-well format in which different immunogens and negative as well as positive controls are immobilized in each well, thus making it possible to screen hundreds of antibody candidates simultaneously. To demonstrate this approach, a model of 4 mixed immunogens immunization was employed. In total, 675 antibody candidates were screened before and after established antibody hybridomas in parallel with immunogen arrays and enzyme-linked immunosorbent assay. The signal intensity, specificity, and cross-reactivity of produced antibody candidates were analyzed using a hierarchical cluster algorithm to track the characteristics of antibody candidates during antibody generation, which might reduce the number of false-positive and false-negative binding of antibodies. Moreover, 4 monoclonal antibodies that were produced successfully recognized their corresponding target antigens.

Detection of His-tagged Long-R³-IGF-I in a black market product

OBJECTIVE

Performance-enhancing substances are illicitly used in elite or amateur sports and may be obtained from the black market due to a cheaper and easier availability. Although various studies have shown that black market products frequently do not contain the declared substances, enormous amounts of illegally produced and/or imported drugs are confiscated from athletes or at customs with alarming results concerning the outcome of the analyses of the ingredients. This case report describes the identification of His-tagged Long-R³-IGF-I, which is usually produced for biochemical studies, in an injection vial.

DESIGN

The ingredients were isolated by immunoaffinity purification and identified by nano-UPLC, high-resolution/high accuracy mass spectrometry of the intact and trypsinated substance and by an enzyme-linked immunosorbent assay.

RESULTS

(Tandem) mass spectra characterized the protein as Long-R³-IGF-I with a His₆-tag attached to the C-terminus by the linker amino acids Leu-Glu.

CONCLUSION

His-tags are commonly added to proteins during synthesis to allow a convenient and complete purification of the final product and His-tags are subsequently removed by specific enzymes when being attached to the N-terminus. The effects of His-tagged Long-R³-IGF-I in humans have not been elucidated or described and the product may rather be a by-product from biochemical studies than synthesized for injection purposes.

Binary polypeptide system for permanent and oriented protein immobilization

BACKGROUND

Many techniques in molecular biology, clinical diagnostics and biotechnology rely on binary affinity tags. The existing tags are based on either small molecules (e.g., biotin/streptavidin or glutathione/GST) or peptide tags (FLAG, Myc, HA, Strep-tag and His-tag). Among these, the biotin-streptavidin system is most popular due to the nearly irreversible interaction of biotin with the tetrameric protein, streptavidin. The major drawback of the stable biotin-streptavidin system, however, is that neither of the two tags can be added to a protein of interest via recombinant means (except for the Strep-tag case) leading to the requirement for chemical coupling.

RESULTS

Here we report a new immobilization system which utilizes two monomeric polypeptides which self-assemble to produce non-covalent yet nearly irreversible complex which is stable in strong detergents, chaotropic agents, as well as in acids and alkali. Our system is based on the core region of the tetra-helical bundle known as the SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptor) complex. This irreversible protein attachment system (IPAS) uses either a shortened syntaxin helix and fused SNAP25-synaptobrevin or a fused syntaxin-synaptobrevin and SNAP25 allowing a two-component system suitable for recombinant protein tagging, capture and immobilization. We also show that IPAS is suitable for use with traditional beads and chromatography, planar surfaces and Biacore, gold nanoparticles and for protein-protein interaction in solution.

CONCLUSIONS

IPAS offers an alternative to chemical cross-linking, streptavidin-biotin system and to traditional peptide affinity tags and can be used for a wide range of applications in nanotechnology and molecular sciences.

Towards proteome scale antibody selections using phage display

In vitro antibody generation by panning a large universal gene library with phage display was employed to generate antibodies to more than 60 different antigens. Of particular interest was a comparison of pannings on 20 different SH2 domains provided by the Structural Genomics Consortium (SGC). Streamlined methods for high throughput antibody generation developed within the 'Antibody Factory' of the German National Genome Research Network (NGFN) were demonstrated to minimise effort and provide a reliable and robust source for antibodies. For the SH2 domains, in two successive series of selections, 2668 clones were analysed, resulting in 347 primary hits in ELISA. Half of these hits were further analysed, and more than 90 different scFv antibodies to all antigens were identified. The validation of selected antibodies by cross-reactivity ELISA, western blot and on protein microarrays demonstrated the versatility of the in vitro antibody selection pipeline to generate a renewable resource of highly specific monoclonal binders in proteome scale numbers with substantially reduced effort and time.

Full dynamic range proteome analysis of S. cerevisiae by targeted proteomics

The rise of systems biology implied a growing demand for highly sensitive techniques for the fast and consistent detection and quantification of target sets of proteins across multiple samples. This is only partly achieved by classical mass spectrometry or affinity-based methods. We applied a targeted proteomics approach based on selected reaction monitoring (SRM) to detect and quantify proteins expressed to a concentration below 50 copies/cell in total S. cerevisiae digests. The detection range can be extended to single-digit copies/cell and to proteins undetected by classical methods. We illustrate the power of the technique by the consistent and fast measurement of a network of proteins spanning the entire abundance range over a growth time course of S. cerevisiae transiting through a series of metabolic phases. We therefore demonstrate the potential of SRM-based proteomics to provide assays for the measurement of any set of proteins of interest in yeast at high-throughput and quantitative accuracy.

Oncoproteomic profiling with antibody microarrays

The incidence of cancer and its associated mortality are increasing globally, indicating an urgent need to develop even more effective and sensitive sets of biomarkers that could help in early diagnosis and consequent intervention. Given that many cellular processes are carried out by proteins, cancer research has recently shifted toward an exploration of the full proteome for such discovery. Among the advanced methodologies that are being developed for analyzing the proteome, antibody microarrays have become a prominent tool for gathering the information required for a better understanding of disease biology, early detection, discrimination of tumors and monitoring of disease progression. Here, we review the technical aspects and challenges in the development and use of antibody microarray assays and examine recently reported applications in oncoproteomics.

From transcriptome analysis to immunogenomics: current status and future direction

In 1994, we pioneered a complementary DNA (cDNA) sequencing project that aimed to predict the primary structures of unknown human proteins. Although our cDNA project was focused on the sequencing of large cDNAs, the following cDNA sequencing projects conducted by other groups have more extensively characterized mammalian transcriptome. In parallel, many groups have made a tremendous amount of effort to develop various resources for functional human genomics. In this context, to demonstrate the power of functional genomic approaches in practice, we have applied them for a comprehensive understanding of the immune system, which we term 'immunogenomics'. This mini-review first describes the historical background of our cDNA project and then provides perspectives on the present and future of immunogenomics based on our experiences.

Chemical and pathway proteomics: powerful tools for oncology drug discovery and personalized health care

In recent years mass spectrometry-based proteomics has moved beyond a mere quantitative description of protein expression levels and their possible correlation with disease or drug action. Impressive progress in LC-MS instrumentation together with the availability of new enabling tools and methods for quantitative proteome analysis and for identification of posttranslational modifications has triggered a surge of chemical and functional proteomics studies dissecting mechanisms of action of cancer drugs and molecular mechanisms that modulate signal transduction pathways. Despite the tremendous progress that has been made in the field, major challenges, relating to sensitivity, dynamic range, and throughput of the described methods, remain. In this review we summarize recent advances in LC-MS-based approaches and their application to cancer drug discovery and to studies of cancer-related pathways in cell culture models with particular emphasis on mechanistic studies of drug action in these systems. Moreover we highlight the emerging utility of pathway and chemical proteomics techniques for translational research in patient tissue.

Immunoaffinity capillary electrophoresis as a powerful strategy for the quantification of low-abundance biomarkers, drugs, and metabolites in biological matrices

In the last few years, there has been a greater appreciation by the scientific community of how separation science has contributed to the advancement of biomedical research. Despite past contributions in facilitating several biomedical breakthroughs, separation sciences still urgently need the development of improved methods for the separation and detection of biological and chemical substances. In particular, the challenging task of quantifying small molecules and biomolecules, found in low abundance in complex matrices (e.g., serum), is a particular area in need of new high-efficiency techniques. The tandem or on-line coupling of highly selective antibody capture agents with the high-resolving power of CE is being recognized as a powerful analytical tool for the enrichment and quantification of ultra-low abundance analytes in complex matrices. This development will have a significant impact on the identification and characterization of many putative biomarkers and on biomedical research in general. Immunoaffinity CE (IACE) technology is rapidly emerging as the most promising method for the analysis of low-abundance biomarkers; its power comes from a three-step procedure: (i) bioselective adsorption and (ii) subsequent recovery of compounds from an immobilized affinity ligand followed by (iii) separation of the enriched compounds. This technology is highly suited to automation and can be engineered to as a multiplex instrument capable of routinely performing hundreds of assays per day. Furthermore, a significant enhancement in sensitivity can be achieved for the purified and enriched affinity targeted analytes. Thus, a compound that exists in a complex biological matrix at a concentration far below its LOD is easily brought to well within its range of quantification. The present review summarizes several applications of IACE, as well as a chronological description of the improvements made in the fabrication of the analyte concentrator-microreactor device leading to the development of a multidimensional biomarker analyzer.

Antibodypedia, a portal for sharing antibody and antigen validation data

Antibodies are useful tools to characterize the components of the human proteome and to validate potential protein biomarkers discovered through various clinical proteomics efforts. The lack of validation results across various applications for most antibodies often makes it necessary to perform cumbersome investigations to ensure specificity of a particular antibody in a certain application. A need therefore exists for a standardized system for sharing validation data about publicly available antibodies and to allow antibody providers as well as users to contribute and edit experimental evidence data, including data also on the antigen. Here we describe a new publicly available portal called Antibodypedia, which has been developed to allow sharing of information regarding validation of antibodies in which providers can submit their own validation results and reliability scores. We report standardized validation criteria and submission rules for applications such as Western blots, protein arrays, immunohistochemistry, and immunofluorescence. The contributor is expected to provide experimental evidence and a validation score for each antibody, and the users can subsequently provide feedback and comments on the use of the antibody. The database thus provides a virtual resource of publicly available antibodies toward human proteins with accompanying experimental evidence supporting an individual validation score for each antibody in an application-specific manner.

Affinity separation and enrichment methods in proteomic analysis

Protein separation or enrichment is one of the rate-limiting steps in proteomic studies. Specific capture and removal of highly-abundant proteins (HAP) with large sample-handling capacities are in great demand for enabling detection and analysis of low-abundant proteins (LAP). How to grasp and enrich these specific proteins or LAP in complex protein mixtures is also an outstanding challenge for biomarker discovery and validation. In response to these needs, various approaches for removal of HAP or capture of LAP in biological fluids, particularly in plasma or serum, have been developed. Among them, immunoaffinity subtraction methods based upon polyclonal IgY or IgG antibodies have shown to possess unique advantages for proteomic analysis of plasma, serum and other biological samples. In addition, other affinity methods that use recombinant proteins, lectins, peptides, or chemical ligands have also been developed and applied to LAP capture or enrichment. This review discusses in detail the need to put technologies and methods in affinity subtraction or enrichment into a context of proteomic and systems biology as "Separomics" and provides a prospective of affinity-mediated proteomics. Specific products, along with their features, advantages, and disadvantages will also be discussed.