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Biomedical subjects

Eckhard Nordhoff

Publications and source records attributed to Eckhard Nordhoff.

8 recordsLinked to original sources

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.

Arabidopsis↗

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.

Computational Biology↗

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.

Arabidopsis Proteins↗

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.

Gene Expression Regulation↗

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.

Adrenocorticotropic Hormone↗

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.

Algorithms↗

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.

Brain↗

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.

Databases, Protein↗