Primary Central Nervous System (CNS) Lymphoma B Cell Receptors Recognize CNS Proteins.

Primary lymphoma of the CNS (PCNSL) is a diffuse large B cell lymphoma confined to the CNS. To elucidate its peculiar organ tropism, we generated recombinant Abs (recAbs) identical to the BCR of 23 PCNSLs from immunocompetent patients. Although none of the recAbs showed self-reactivity upon testing with common autoantigens, they recognized 1547 proteins present on a large-scale protein microarray, indicating polyreactivity. Interestingly, proteins (GRINL1A, centaurin-α, BAIAP2) recognized by the recAbs are physiologically expressed by CNS neurons. Furthermore, 87% (20/23) of the recAbs, including all Abs derived from IGHV4-34 using PCNSL, recognized galectin-3, which was upregulated on microglia/macrophages, astrocytes, and cerebral endothelial cells upon CNS invasion by PCNSL. Thus, PCNSL Ig may recognize CNS proteins as self-Ags. Their interaction may contribute to BCR signaling with sustained NF-κB activation and, ultimately, may foster tumor cell proliferation and survival. These data may also explain, at least in part, the affinity of PCNSL cells for the CNS.

Improving the default data analysis workflow for large autoimmune biomarker discovery studies with ProtoArrays.

Contemporary protein microarrays such as the ProtoArray® are used for autoimmune antibody screening studies to discover biomarker panels. For ProtoArray data analysis, the software Prospector and a default workflow are suggested by the manufacturer. While analyzing a large data set of a discovery study for diagnostic biomarkers of the Parkinson's disease (ParkCHIP), we have revealed the need for distinct improvements of the suggested workflow concerning raw data acquisition, normalization and preselection method availability, batch effects, feature selection, and feature validation. In this work, appropriate improvements of the default workflow are proposed. It is shown that completely automatic data acquisition as a batch, a re-implementation of Prospector's pre-selection method, multivariate or hybrid feature selection, and validation of the selected protein panel using an independent test set define in combination an improved workflow for large studies.

Optimal precursor ion selection for LC-MALDI MS/MS.

BACKGROUND: Liquid chromatography mass spectrometry (LC-MS) maps in shotgun proteomics are often too complex to select every detected peptide signal for fragmentation by tandem mass spectrometry (MS/MS). Standard methods for precursor ion selection, commonly based on data dependent acquisition, select highly abundant peptide signals in each spectrum. However, these approaches produce redundant information and are biased towards high-abundance proteins. RESULTS: We present two algorithms for inclusion list creation that formulate precursor ion selection as an optimization problem. Given an LC-MS map, the first approach maximizes the number of selected precursors given constraints such as a limited number of acquisitions per RT fraction. Second, we introduce a protein sequence-based inclusion list that can be used to monitor proteins of interest. Given only the protein sequences, we create an inclusion list that optimally covers the whole protein set. Additionally, we propose an iterative precursor ion selection that aims at reducing the redundancy obtained with data dependent LC-MS/MS. We overcome the risk of erroneous assignments by including methods for retention time and proteotypicity predictions. We show that our method identifies a set of proteins requiring fewer precursors than standard approaches. Thus, it is well suited for precursor ion selection in experiments with limited sample amount or analysis time. CONCLUSIONS: We present three approaches to precursor ion selection with LC-MALDI MS/MS. Using a well-defined protein standard and a complex human cell lysate, we demonstrate that our methods outperform standard approaches. Our algorithms are implemented as part of OpenMS and are available under http://www.openms.de.

Synthesis of S-adenosyl-L-homocysteine capture compounds for selective photoinduced isolation of methyltransferases.

Understanding the interplay of different cellular proteins and their substrates is of major interest in the postgenomic era. For this purpose, selective isolation and identification of proteins from complex biological samples is necessary and targeted isolation of enzyme families is a challenging task. Over the last years, methods like activity-based protein profiling (ABPP) and capture compound mass spectrometry (CCMS) have been developed to reduce the complexity of the proteome by means of protein function in contrast to standard approaches, which utilize differences in physical properties for protein separation. To isolate and identify the subproteome consisting of S-adenosyl-L-methionine (SAM or AdoMet)-dependent methyltransferases (methylome), we developed and synthesized trifunctional capture compounds containing the chemically stable cofactor product S-adenosyl-L-homocysteine (SAH or AdoHcy) as selectivity function. SAH analogues with amino linkers at the N6 or C8 positions were synthesized and attached to scaffolds containing different photocrosslinking groups for covalent protein modification and biotin for affinity isolation. The utility of these SAH capture compounds for selective photoinduced protein isolation is demonstrated for various methyltransferases (MTases) acting on DNA, RNA and proteins as well as with Escherichia coli cell lysate. In addition, they can be used to determine dissociation constants for MTase-cofactor complexes.

High-throughput proteomics using matrix-assisted laser desorption/ ionization mass spectrometry.

It has become evident that the mystery of life will not be deciphered just by decoding its blueprint, the genetic code. In the life and biomedical sciences, research efforts are now shifting from pure gene analysis to the analysis of all biomolecules involved in the machinery of life. One area of these postgenomic research fields is proteomics. Although proteomics, which basically encompasses the analysis of proteins, is not a new concept, it is far from being a research field that can rely on routine and large-scale analyses. At the time the term proteomics was coined, a gold-rush mentality was created, promising vast and quick riches (i.e., solutions to the immensely complex questions of life and disease). Predictably, the reality has been quite different. The complexity of proteomes and the wide variations in the abundances and chemical properties of their constituents has rendered the use of systematic analytical approaches only partially successful, and biologically meaningful results have been slow to arrive. However, to learn more about how cells and, hence, life works, it is essential to understand the proteins and their complex interactions in their native environment. This is why proteomics will be an important part of the biomedical sciences for the foreseeable future. Therefore, any advances in providing the tools that make protein analysis a more routine and large-scale business, ideally using automated and rapid analytical procedures, are highly sought after. This review will provide some basics, thoughts and ideas on the exploitation of matrix-assisted laser desorption/ ionization in biological mass spectrometry - one of the most commonly used analytical tools in proteomics - for high-throughput analyses.

Highly immunoreactive IgG antibodies directed against a set of twenty human proteins in the sera of patients with amyotrophic lateral sclerosis identified by protein array.

Amyotrophic lateral sclerosis (ALS), the most common adult-onset motor neuron disorder, is characterized by the progressive and selective loss of upper and lower motor neurons. Diagnosis of this disorder is based on clinical assessment, and the average survival time is less than 3 years. Injections of IgG from ALS patients into mice are known to specifically mark motor neurons. Moreover, IgG has been found in upper and lower motor neurons in ALS patients. These results led us to perform a case-control study using human protein microarrays to identify the antibody profiles of serum samples from 20 ALS patients and 20 healthy controls. We demonstrated high levels of 20 IgG antibodies that distinguished the patients from the controls. These findings suggest that a panel of antibodies may serve as a potential diagnostic biomarker for ALS.

LGALS3BP regulates centriole biogenesis and centrosome hypertrophy in cancer cells.

Centrosome morphology and number are frequently deregulated in cancer cells. Here, to identify factors that are functionally relevant for centrosome abnormalities in cancer cells, we established a protein-interaction network around 23 centrosomal and cell-cycle regulatory proteins, selecting the interacting proteins that are deregulated in cancer for further studies. One of these components, LGALS3BP, is a centriole- and basal body-associated protein with a dual role, triggering centrosome hypertrophy when overexpressed and causing accumulation of centriolar substructures when downregulated. The cancer cell line SK-BR-3 that overexpresses LGALS3BP exhibits hypertrophic centrosomes, whereas in seminoma tissues with low expression of LGALS3BP, supernumerary centriole-like structures are present. Centrosome hypertrophy is reversed by depleting LGALS3BP in cells endogenously overexpressing this protein, supporting a direct role in centrosome aberration. We propose that LGALS3BP suppresses assembly of centriolar substructures, and when depleted, causes accumulation of centriolar complexes comprising CPAP, acetylated tubulin and centrin.

An iterative strategy for precursor ion selection for LC-MS/MS based shotgun proteomics.

Currently, the precursor ion selection strategies in LC-MS mainly choose the most prominent peptide signals for MS/MS analysis. Consequently, high-abundance proteins are identified by MS/MS of many peptides, whereas proteins of lower abundance might elude identification. We present a novel, iterative and result-driven approach for precursor ion selection that significantly increases the efficiency of an MS/MS analysis by decreasing data redundancy and analysis time. By simulating different strategies for precursor ion selection on an existing data set, we compare our method to existing result-driven strategies and evaluate its performance with regard to mass accuracy, database size, and sample complexity.

Characterization of tau in cerebrospinal fluid using mass spectrometry.

The neurodegenerative disorder Alzheimer's disease (AD) is the most common cause of dementia in the elderly. The presence of neurofibrillary tangles, consisting of hyperphosphorylated tau protein, is one of the major neuropathologic characteristics of the disease, making this protein an attractive biomarker for AD and a possible target for therapy. Here, we describe an optimized immunoprecipitation mass spectrometry method that enables, for the first time, detailed characterization of tau in human cerebrospinal fluid. The identities of putative tau fragments were confirmed using nanoflow liquid chromatography and tandem mass spectrometry. Nineteen tryptic fragments of tau were detected, of which 16 are found in all tau isoforms while 3 represented unique tau isoforms. These results pave the way for clinical CSF studies on the tauopathies.

Identification and characterization of DNA-binding proteins by mass spectrometry.

Mass spectrometry is the most sensitive and specific analytical technique available for protein identification and quantification. Over the past 10 years, by the use of mass spectrometric techniques hundreds of previously unknown proteins have been identified as DNA-binding proteins that are involved in the regulation of gene expression, replication, or DNA repair. Beyond this task, the applications of mass spectrometry cover all aspects from sequence and modification analysis to protein structure, dynamics, and interactions. In particular, two new, complementary ionization techniques have made this possible: matrix-assisted laser desorption/ionization and electrospray ionization. Their combination with different mass-over-charge analyzers and ion fragmentation techniques, as well as specific enzymatic or chemical reactions and other analytical techniques, has led to the development of a broad repertoire of mass spectrometric methods that are now available for the identification and detailed characterization of DNA-binding proteins. These techniques, how they work, what their requirements and limitations are, and selected examples that document their performance are described and discussed in this chapter.

Proteome analysis of Arabidopsis thaliana by two-dimensional gel electrophoresis and matrix-assisted laser desorption/ionisation-time of flight mass spectrometry.

In the present study we show results of a large-scale proteome analysis of the recently sequenced plant Arabidopsis thaliana. On the basis of a previously published sequential protein extraction protocol, we prepared protein extracts from eight different A. thaliana tissues (primary leaf, leaf, stem, silique, seedling, seed, root, and inflorescence) and analysed these by two-dimensional gel electrophoresis. A total of 6000 protein spots, from three of these tissues, namely primary leaf, silique and seedling, were excised and the contained proteins were analysed by matrix assisted laser desorption/ionisation time of flight mass spectrometry peptide mass fingerprinting. This resulted in the identification of the proteins contained in 2943 spots, which were found to be products of 663 different genes. In this report we present and discuss the methodological and biological results of our plant proteome analysis.

Protein arrays and their role in proteomics.

Arraying technologies have shown the way to smaller sample volumes, more efficient analyses and higher throughput. Proteomics is a field, which has grown in significance in the last five years. This review outlines recent developments in protein arrays and their applications in proteomics, and discusses the requirements, current limitations and the potential and future perspectives of the technology.

A calibration method that simplifies and improves accurate determination of peptide molecular masses by MALDI-TOF MS.

The use of delayed ion extraction in MALDI time-of-flight mass spectrometry distorts the linear relationship between m/z and the square of the ion flight time (t2) with the consequence that, if a mass accuracy of 10 ppm or better is to be obtained, the calibrant signals have to fall close to the analyte signals. If this is not possible, systematic errors arise. To eliminate these, a higher-order calibration function and thus several calibrant signals are required. For internal calibration, however, this approach is limited by signal suppression effects and the increasing chance of the calibrant signals overlapping with analyte signals. If instead the calibrants are prepared separately, this problem is replaced by an other; i.e., the ion flight times are dependent on the sample plate position. For this reason, even if the calibrants are placed close to the sample, the mass accuracy is not improved when a higher-order calibration function is applied. We have studied this phenomenon and found that the relative errors, which result when moving from one sample to the next, are directly proportional to m/z. Based on this observation, we developed a two-step calibration method, that overcomes said limitations. The first step is an external calibration with a high-order polynomial function used for the determination of the relation between m/z and t2, and the second step is a first-order internal correction for sample position-dependent errors. Applying this method, for instance, to a mass spectrum of a mixture of 18 peptides from a tryptic digest of a recombinant protein resulted in an average mass error of 1.0 ppm with a standard deviation of 3.5 ppm. When instead using a conventional two-point internal calibration, the average relative error was 2.2 ppm with a standard deviation of 15 ppm. The new method is described and its performance is demonstrated with examples relevant to proteome research.

Protein identification by MALDI-TOF-MS peptide mapping: a new strategy.

A new strategy for identifying proteins by MALDI-TOF-MS peptide mapping is reported. In contrast to current approaches, the strategy does not rely on a good relative or absolute mass accuracy as the criterion that discriminates false positive results. The protein sequence database is first searched for all proteins that match a minimum five of the submitted masses within the maximum expected relative errors when the default or externally determined calibration constants are used, for instance, +/-500 ppm. Typically, this search retrieves many thousand candidate sequences. Assuming initially that each of these is the correct protein, the relative errors of the matching peptide masses are calculated for each candidate sequence. Linear regression analysis is then performed of the calculated relative errors as a function of m/z for each candidate sequence, and the standard deviation to the regression is used to distinguish the correct sequence among the candidates. We show that this parameter is independent of whether the mass spectrometric data were internally or externally calibrated. The result is a search engine that renders internal spectrum calibration unnecessary and adapts to the quality of the raw data without user interference. This is made possible by a dynamic scoring algorithm, which takes into account the number of matching peptide masses, the percentage of the protein's sequence covered by these peptides and, as new parameter, the determined standard deviation. The lower the standard deviation, the less cleavage peptides are required for identification and vice versa. Performance of the new strategy is demonstrated and discussed. All necessary computing has been implemented in a computer program, free access to which is provided in the Internet.

Extraction of proteins from plant tissues for two-dimensional electrophoresis analysis.

To increase the number of proteins detectable by two-dimensional electrophoresis (2-DE) in plants, we present a new procedure for extracting total proteins from plant tissue. This method avoids any loss of proteins in the course of sample preparation and results in two different fractions, one comprising mainly the cytoplasmatic proteins, the other one containing predominantly structure bond proteins. 2-DE patterns obtained from these two fractions show that the total number of different protein spots detected exceeds the degree of resolution commonly reported for plant proteins threefold.

Protein array technology: the tool to bridge genomics and proteomics.

The generation of protein chips requires much more efforts than DNA microchips. While DNA is DNA and a variety of different DNA molecules behave stable in a hybridisation experiment, proteins are much more difficult to produce and to handle. Outside of a narrow range of environmental conditions, proteins will denature, lose their three-dimensional structure and a lot of their specificity and activity. The chapter describes the pitfalls and challenges in Protein Microarray technology to produce native and functional proteins and store them in a native and special environment for every single spot on an array, making applications like antibody profiling and serum screening possible not only on denatured arrays but also on native protein arrays.

Generation of minimal protein identifiers of proteins from two-dimensional gels and recombinant proteins.

We describe the technical feasibility and methodology to characterize a protein by a minimal set of structural information generated by matrix assisted laser desorption/ionization (MALDI)-mass spectrometry, termed a "minimal protein Identifier" (MPI). MPIs can be determined for proteins from two-dimensional gels and recombinant proteins and can be used to compare and identify proteins from these sources.