Biomedical subjects

Roland Krause

Publications and source records attributed to Roland Krause.

10 recordsLinked to original sources

PubMed2007

Identification of tightly regulated groups of genes during Drosophila melanogaster embryogenesis.

Time-series analysis of whole-genome expression data during Drosophila melanogaster development indicates that up to 86% of its genes change their relative transcript level during embryogenesis. By applying conservative filtering criteria and requiring 'sharp' transcript changes, we identified 1534 maternal genes, 792 transient zygotic genes, and 1053 genes whose transcript levels increase during embryogenesis. Each of these three categories is dominated by groups of genes where all transcript levels increase and/or decrease at similar times, suggesting a common mode of regulation. For example, 34% of the transiently expressed genes fall into three groups, with increased transcript levels between 2.5-12, 11-20, and 15-20 h of development, respectively. We highlight common and distinctive functional features of these expression groups and identify a coupling between downregulation of transcript levels and targeted protein degradation. By mapping the groups to the protein network, we also predict and experimentally confirm new functional associations.

Analysis of Variance↗

PubMed2006

Proteome survey reveals modularity of the yeast cell machinery.

Protein complexes are key molecular entities that integrate multiple gene products to perform cellular functions. Here we report the first genome-wide screen for complexes in an organism, budding yeast, using affinity purification and mass spectrometry. Through systematic tagging of open reading frames (ORFs), the majority of complexes were purified several times, suggesting screen saturation. The richness of the data set enabled a de novo characterization of the composition and organization of the cellular machinery. The ensemble of cellular proteins partitions into 491 complexes, of which 257 are novel, that differentially combine with additional attachment proteins or protein modules to enable a diversification of potential functions. Support for this modular organization of the proteome comes from integration with available data on expression, localization, function, evolutionary conservation, protein structure and binary interactions. This study provides the largest collection of physically determined eukaryotic cellular machines so far and a platform for biological data integration and modelling.

Genome, Fungal↗

PubMed2006

Identifying protein complexes in high-throughput protein interaction screens using an infinite latent feature model.

We propose a Bayesian approach to identify protein complexes and their constituents from high-throughput protein-protein interaction screens. An infinite latent feature model that allows for multi-complex membership by individual proteins is coupled with a graph diffusion kernel that evaluates the likelihood of two proteins belonging to the same complex. Gibbs sampling is then used to infer a catalog of protein complexes from the interaction screen data. An advantage of this model is that it places no prior constraints on the number of complexes and automatically infers the number of significant complexes from the data. Validation results using affinity purification/mass spectrometry experimental data from yeast RNA-processing complexes indicate that our method is capable of partitioning the data in a biologically meaningful way. A supplementary web site containing larger versions of the figures is available at http://public.kgi.edu/wild/PSBO6/index.html.

Algorithms↗

PubMed2004

Modular decomposition of protein-protein interaction networks.

We introduce an algorithmic method, termed modular decomposition, that defines the organization of protein-interaction networks as a hierarchy of nested modules. Modular decomposition derives the logical rules of how to combine proteins into the actual functional complexes by identifying groups of proteins acting as a single unit (sub-complexes) and those that can be alternatively exchanged in a set of similar complexes. The method is applied to experimental data on the pro-inflammatory tumor necrosis factor-alpha (TNF-alpha)/NFkappaB transcription factor pathway.

Algorithms↗

PubMed2004

Shared components of protein complexes--versatile building blocks or biochemical artefacts?

Protein complexes perform many important functions in the cell. Large-scale studies of protein-protein interactions have not only revealed new complexes but have also placed many proteins into multiple complexes. Whilst the advocates of hypothesis-free research touted the discovery of these shared components as new links between diverse cellular processes, critical commentators denounced many of the findings as artefacts, thus questioning the usefulness of large-scale approaches. Here, we survey proteins known to be shared between complexes, as established in the literature, and compare them to shared components found in high-throughput screens. We discuss the various challenges to the identification and functional interpretation of bona fide shared components, namely contaminants, variant and megacomplexes, and transient interactions, and suggest that many of the novel shared components found in high-throughput screens are neither the results of contamination nor central components, but appear to be primarily regulatory links in cellular processes.

Algorithms↗

PubMed2004

Finite-element analysis of material and parameter effects in laser-based thermoelastic ultrasound generation.

Laser-based, thermoelastic transduction methods have potential in very high frequency (>50 MHz), high-density two-dimensional (2-D) arrays for a variety of very high-resolution superficial imaging applications, including in vivo tissue sectioning. Previous studies of these transducers generally have been based on experimental measurements or theoretical analyses using various simplifying assumptions. These theoretical models are mostly 1-D and best matched to simple geometries with a minimum number of component materials. In this work, we use a new thermoelastic solver in a commercially available finite-element analysis (FEA) software package to analyze multidimensional effects in laser-based devices of arbitrary geometry with the potential for use with arbitrary material properties. The FEA approach was verified first against experimental data. Thereafter, we explored the impact of various design variables, including laser spot size and laser penetration depth.

Anatomy, Cross-Sectional↗

PubMed2003

A comprehensive set of protein complexes in yeast: mining large scale protein-protein interaction screens.

MOTIVATION: The analysis of protein-protein interactions allows for detailed exploration of the cellular machinery. The biochemical purification of protein complexes followed by identification of components by mass spectrometry is currently the method, which delivers the most reliable information--albeit that the data sets are still difficult to interpret. Consolidating individual experiments into protein complexes, especially for high-throughput screens, is complicated by many contaminants, the occurrence of proteins in otherwise dissimilar purifications due to functional re-use and technical limitations in the detection. A non-redundant collection of protein complexes from experimental data would be useful for biological interpretation, but manual assembly is tedious and often inconsistent. RESULTS: Here, we introduce a measure to define similarity within collections of purifications and generate a set of minimally redundant, comprehensive complexes using unsupervised clustering. AVAILABILITY: Programs and results are freely available from http://www.bork.embl-heidelberg.de/Docu/purclust/

Algorithms↗

PubMed2003

NRSAS: Nuclear Receptor Structure Analysis Servers.

We present a coherent series of servers that can perform a large number of structure analyses on nuclear hormone receptors. These servers are part of the NucleaRDB project, which provides a powerful information system for nuclear hormone receptors. The computations performed by the servers include homology modelling, structure validation, calculating contacts, accessibility values, hydrogen bonding patterns, predicting mutations and a host of two- and three-dimensional visualisations. The Nuclear Receptor Structure Analysis Servers (NRSAS) are freely accessible at http://www.cmbi.kun.nl/NR/servers/html/ and in-house copies can be obtained upon request.

Hormones↗

PubMed2002

Comparative assessment of large-scale data sets of protein-protein interactions.

Comprehensive protein protein interaction maps promise to reveal many aspects of the complex regulatory network underlying cellular function. Recently, large-scale approaches have predicted many new protein interactions in yeast. To measure their accuracy and potential as well as to identify biases, strengths and weaknesses, we compare the methods with each other and with a reference set of previously reported protein interactions.

Bias↗

PubMed2002

Functional organization of the yeast proteome by systematic analysis of protein complexes.

Most cellular processes are carried out by multiprotein complexes. The identification and analysis of their components provides insight into how the ensemble of expressed proteins (proteome) is organized into functional units. We used tandem-affinity purification (TAP) and mass spectrometry in a large-scale approach to characterize multiprotein complexes in Saccharomyces cerevisiae. We processed 1,739 genes, including 1,143 human orthologues of relevance to human biology, and purified 589 protein assemblies. Bioinformatic analysis of these assemblies defined 232 distinct multiprotein complexes and proposed new cellular roles for 344 proteins, including 231 proteins with no previous functional annotation. Comparison of yeast and human complexes showed that conservation across species extends from single proteins to their molecular environment. Our analysis provides an outline of the eukaryotic proteome as a network of protein complexes at a level of organization beyond binary interactions. This higher-order map contains fundamental biological information and offers the context for a more reasoned and informed approach to drug discovery.

Cells, Cultured↗