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.

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.

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.

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.

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.

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.