Antibody-based tissue profiling as a tool for clinical proteomics

Here, we show a strategy for high-throughput antibody-based tissue profiling with the aim to create an atlas of protein expression patterns in normal human tissues and cancer tissues representing the 20 most prevalent cancer types. A set of standardized tissue microarrays (TMAs) was produced to allow for rapid screening of a multitude of different cells and tissues using immunohistochemistry. Eight TMA blocks were produced containing 48 different normal human tissues in triplicate and cancer tissue from 216 individually different tumors in duplicate. Sections from these blocks were immunohistochemically stained using five commercial and five in-house generated antibodies. Digital images for annotation of expression profiles were generated using a semiautomated approach. Five hundred seventy-six images and annotation data corresponding to a total of 30 Gbytes of data were collected for each antibody. The data presented here suggest that antibody-based profiling of protein expression in tissues can be used as a valuable tool in clinical proteomics.     

Proteomic profiling of mechanistically distinct enzyme classes using a common chemotype

Proteomics research requires methods to characterize the expression and function of proteins in complex mixtures. Toward this end, chemical probes that incorporate known affinity labeling agents have facilitated the activity-based profiling of certain enzyme families. To accelerate the discovery of proteomics probes for enzyme classes lacking cognate affinity labels, we describe here a combinatorial strategy. Members of a probe library bearing a sulfonate ester chemotype were screened against complex proteomes for activity-dependent protein reactivity, resulting in the labeling of at least six mechanistically distinct enzyme classes. Surprisingly, none of these enzymes represented targets of previously described proteomics probes. The sulfonate library was used to identify an omega-class glutathione S-transferase whose activity was upregulated in invasive human breast cancer lines. These results indicate that activity-based probes compatible with whole-proteome analysis can be developed for numerous enzyme classes and applied to identify enzymes associated with discrete pathological states.     

Towards a human proteome atlas: high-throughput generation of mono-specific antibodies for tissue profiling

A great need exists for the systematic generation of specific antibodies to explore the human proteome. Here, we show that antibodies specific to human proteins can be generated in a high-throughput manner involving stringent affinity purification using recombinant protein epitope signature tags (PrESTs) as immunogens and affinity-ligands. The specificity of the generated affinity reagents, here called mono-specific antibodies (msAb), were validated with a novel protein microarray assay. The success rate for 464 antibodies generated towards human proteins was more than 90% as judged by the protein array assay. The antibodies were used for parallel profiling of patient biopsies using tissue microarrays generated from 48 human tissues. Comparative analysis with well-characterized monoclonal antibodies showed identical or similar specificity and expression patterns. The results suggest that a comprehensive atlas containing extensive protein expression and subcellular localization data of the human proteome can be generated in an efficient manner with mono-specific antibodies.     

Approaches for systematic proteome exploration

With the completion of the human genome project (HUGO) during recent years, gene function, protein abundance and expression patterns in tissues and cell types have emerged as central areas for the scientific community. A mapped human proteome will extend the value of the genome sequence and large-scale efforts aiming at elucidating protein localization, abundance and function are invaluable for biomarker and drug discovery. This research area, termed proteomics, is more demanding than any genome sequencing effort and to perform this on a wide scale is a highly diverse task. Therefore, the proteomics field employs a range of methods to examine different aspects of proteomics including protein localization, protein-protein interactions, posttranslational modifications and alteration of protein composition (e.g. differential expression) in tissues and body fluids. Here, some of the most commonly used methods, including chromatographic separations together with mass spectrometry and a number of affinity proteomics concepts are discussed and exemplified.     

A human protein atlas for normal and cancer tissues based on antibody proteomics

Antibody-based proteomics provides a powerful approach for the functional study of the human proteome involving the systematic generation of protein-specific affinity reagents. We used this strategy to construct a comprehensive, antibody-based protein atlas for expression and localization profiles in 48 normal human tissues and 20 different cancers. Here we report a new publicly available database containing, in the first version, approximately 400,000 high resolution images corresponding to more than 700 antibodies toward human proteins. Each image has been annotated by a certified pathologist to provide a knowledge base for functional studies and to allow queries about protein profiles in normal and disease tissues. Our results suggest it should be possible to extend this analysis to the majority of all human proteins thus providing a valuable tool for medical and biological research.     

Quantitative protein profiling using two-dimensional gel electrophoresis,isotope-coded affinity tag labeling,and mass spectrometry

Quantitative protein profiling is an essential part of proteomics and requires new technologies that accurately, reproducibly, and comprehensively identify and quantify the proteins contained in biological samples. We describe a new strategy for quantitative protein profiling that is based on the separation of proteins labeled with isotope-coded affinity tag reagents by two-dimensional gel electrophoresis and their identification and quantification by mass spectrometry. The method is based on the observation that proteins labeled with isotopically different isotope-coded affinity tag reagents precisely co-migrate during two-dimensional gel electrophoresis and that therefore two or more isotopically encoded samples can be separated concurrently in the same gel. By analyzing changes in the proteome of yeast (Saccharomyces cerevisiae) induced by a metabolic shift we show that this simple method accurately quantifies changes in protein abundance even in cases in which multiple proteins migrate to the same gel coordinates. The method is particularly useful for the quantitative analysis and structural characterization of differentially processed or post-translationally modified forms of a protein and is therefore expected to find wide application in proteomics research.     

From gene expression analysis to tissue microarrays: a rational approach to identify therapeutic and diagnostic targets in lymphoid malignancies

Mantle cell lymphoma (MCL) is an aggressive lymphoid malignancy for which better treatment strategies are needed. To identify potential diagnostic and therapeutic targets, a signature consisting of MCL-associated genes was selected based on a comprehensive gene expression analysis of malignant and normal B cells. The corresponding protein epitope signature tags were identified and used to raise monospecific, polyclonal antibodies, which were subsequently analyzed on paraffin-embedded sections of malignant and normal tissue. In this study, we demonstrate that the initial selection strategy of MCL-associated genes successfully allows identification of protein antigens either uniquely expressed or overexpressed in MCL compared with normal lymphoid tissues. We propose that genome-based, affinity proteomics, using protein epitope signature tag-induced antibodies, is an efficient way to rapidly identify a number of disease-associated protein candidates of both previously known and unknown identities.     

A multiple reaction monitoring method for absolute quantification of the human liver alcohol dehydrogenase ADH1C1 isoenzyme

Although significant progress has been made in protein quantification using mass spectrometry during recent years, absolute protein quantification in complex biological systems remains a challenging task in proteomics. The use of stable isotope-labeled standard peptide is the most commonly used strategy for absolute quantification, but it might not be suitable in all instances. Here we report an alternative strategy that employs a stable isotope-labeled intact protein as an internal standard to absolutely quantify the alcohol dehydrogenase (ADH) expression level in a human liver sample. In combination with a new targeted proteomics approach employing the method of multiple reaction monitoring (MRM), we precisely and quantitatively measured the absolute protein expression level of an ADH isoenzyme, ADH1C1, in human liver. Isotope-labeled protein standards are predicted to be particularly useful for measurement of highly homologous isoenzymes such as ADHs where multiple signature peptides can be examined by MRM in a single experiment.     

Engineering HlyA hypersecretion in Escherichia coli based on proteomic and microarray analyses

Escherichia coli is a common host for recombinant protein production for biotechnology applications. Secretion to the extracellular media has the potential to reduce protein aggregation and to simplify downstream purification. However, the complexity of the mechanisms of protein secretion has confounded prior attempts to engineer enhanced secretion phenotypes. Here, mutagenesis was used to perturb E. coli W3110 cells secreting HlyA via a Type I pathway. An activity assay identified a mutant secreting fourfold more active alpha-hemolysin than the parent strain. The mutant was characterized using both high-density microarrays for mRNA profiling and a proteomics strategy for protein expression. The relative mRNA and protein expression levels of tRNA-synthetases were decreased in the mutant compared to the parent. A mathematical model of prokaryotic translation was used to design a variant of the hlyA gene that encodes the same amino acid sequence but uses rare codons to slow the rate of translation by altering five bases. Analysis of the parent strain transformed with a plasmid containing this variant gene resulted in the recovery of, and further improvement upon, the selected hypersecretion phenotype. These results present one of the first successful metabolic engineering attempts based on molecular information provided by mRNA and protein expression profiling approaches and resulting in a phenotype useful to the biotechnology community.     

Selected expression profiling of full-length proteins and their variants in human plasma

With increased interest in clinical proteomics—the comparative investigation of differential protein expression patterns for use in the diagnostic and prognostic assessment of disease states—the demand for techniques that can readily identify changes in select proteome components is greater than ever before. This article describes a targeted proteomics approach to recover and quantify C-reactive protein (CRP) directly from human plasma. CRP, a putative biomarker for cardiac health, was isolated from microliter volumes of human plasma by using novel proteomics tools that combine micro-scale affinity capture with matrix assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) detection. Native CRP was analyzed along with serum amyloid P component (SAP) and retinol binding protein (RBP), that were intentionally targeted to generate a selected protein expression profile. A number of qualitative changes were readily observed within these profiles, including micro heterogeneity in the SAP glycan, C-terminally truncated versions of RBP, and detection of a novel truncated variant of CRP. After quantitative validation of increasing plasma CRP concentrations, the approach was applied to the analysis of eight plasma samples obtained from individuals with known medical histories. The result of the analyses are eight protein profiles, revealing increasing CRP levels that can be associated with individuals ailing from post-surgery inflammation, chronic rheumatoid arthritis, and recent acute myocardial infarction. The technique described in this article lays the foundation for selected protein profiling for use in biomarker discovery, as well as in clinical and diagnostic applications.     

A streamlined platform for high-content functional proteomics of primary human specimens

Achieving information content of satisfactory breadth and depth remains a formidable challenge for proteomics. This problem is particularly relevant to the study of primary human specimens, such as tumor biopsies, which are heterogeneous and of finite quantity. Here we present a functional proteomics strategy that unites the activity-based protein profiling and multidimensional protein identification technologies (ABPP-MudPIT) for the streamlined analysis of human samples. This convergent platform involves a rapid initial phase, in which enzyme activity signatures are generated for functional classification of samples, followed by in-depth analysis of representative members from each class. Using this two-tiered approach, we identified more than 50 enzyme activities in human breast tumors, nearly a third of which represent previously uncharacterized proteins. Comparison with cDNA microarrays revealed enzymes whose activity, but not mRNA expression, depicted tumor class, underscoring the power of ABPP-MudPIT for the discovery of new markers of human disease that may evade detection by other molecular profiling methods.     

Biomedical applications of protein chips

The development of microchips involving proteins has accelerated within the past few years. Although DNA chip technologies formed the precedent, many different strategies and technologies have been used because proteins are inherently a more complex type of molecule. This review covers the various biomedical applications of protein chips in diagnostics, drug screening and testing, disease monitoring, drug discovery (proteomics), and medical research. The proteomics and drug discovery section is further subdivided to cover drug discovery tools (on-chip separations, expression profiling, and antibody arrays), molecular interactions and signaling pathways, the identification of protein function, and the identification of novel therapeutic compounds. Although largely focused on protein chips, this review includes chips involving cells and tissues as a logical extension of the type of data that can be generated from these microchips.     

Profiling proteoforms: promising follow-up of proteomics for biomarker discovery

Today, proteomics usually compares clinical samples by use of bottom-up profiling with high resolution mass spectrometry, where all protein products of a single gene are considered as an integral whole. At the same time, proteomics of proteoforms, which considers the variety of protein species, offers the potential to discover valuable biomarkers. Proteoforms are protein species that arise as a consequence of genetic polymorphisms, alternative splicing, post-translational modifications and other less-explored molecular events. The comprehensive observation of proteoforms has been an exclusive privilege of top-down proteomics. Here, we review the possibilities of a bottom-up approach to address the microheterogeneity of the human proteome. Special focus is given to shotgun proteomics and structure-based bioinformatics as a source of hypothetical proteoforms, which can potentially be verified by targeted mass spectrometry to determine the relevance of proteoforms to diseases.