Kay Nieselt
Research interests
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InterestsTranscriptomics, Data Analysis, R, Statistical Analysis, Gene Expression, Next Generation Sequencing, Genomics, Bioinformatic Tools, Microarray, Gene Regulation, Visualization, sRNAs
Publications
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3.94Impact points
Phylogeny of the staphylococcal major autolysin (Atl) and its use in genus and species typing.
Journal of bacteriology. 03/2012;
The major staphylococcal autolysin Atl is an important player in cell separation and daughter cell formation. In this study we investigated the amino acid sequences of Atl derived from 15 staphylococcal and one macrococcal species representatives. The overall organization of the bifunctional precurs... [more] The major staphylococcal autolysin Atl is an important player in cell separation and daughter cell formation. In this study we investigated the amino acid sequences of Atl derived from 15 staphylococcal and one macrococcal species representatives. The overall organization of the bifunctional precursor protein consisting of signal peptide (SP), propeptide (PP), amidase (AM), six repeat sequences (R(1-6)), and glucosaminidase (GL) was highly conserved in all species. The most-conserved domains were the enzyme domains AM and GL; the least conserved regions were the PP and the R-regions. An Atl-based phylogenetic tree for the various species representatives correlated well with the corresponding 16S-rRNA-based tree from the literature and also matched perfectly with the phylogenetic trees based on core genome analysis. The phylogenetic distance analysis of 18 AtlA proteins of various S. aureus strains and 15 AtlE proteins of S. epidermidis revealed that both species representatives formed a relatively homogeneous cluster. Two S. epidermidis strains, M23864:W1 and VCU116, were identified by Atl-typing that clustered far more distantly and belonged to either S. caprae and S. capitis or a new sub-species. Here we show that Atl-typing is a useful tool for staphylococcal genus and species typing by using either the highly conserved AM or the less conserved PP domains.
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8.35Impact points
Metabolic Switches and Adaptations Deduced from the Proteomes of Streptomyces coelicolor Wild Type and phoP Mutant Grown in Batch Culture.
Molecular & cellular proteomics : MCP. 12/2011; 11(2):M111.013797.
Bacteria in the genus Streptomyces are soil-dwelling oligotrophs and important producers of secondary metabolites. Previously, we showed that global messenger RNA expression was subject to a series of metabolic and regulatory switches during the lifetime of a fermentor batch culture of Streptomyces ... [more] Bacteria in the genus Streptomyces are soil-dwelling oligotrophs and important producers of secondary metabolites. Previously, we showed that global messenger RNA expression was subject to a series of metabolic and regulatory switches during the lifetime of a fermentor batch culture of Streptomyces coelicolor M145. Here we analyze the proteome from eight time points from the same fermentor culture and, because phosphate availability is an important regulator of secondary metabolite production, compare this to the proteome of a similar time course from an S. coelicolor mutant, INB201 (ΔphoP), defective in the control of phosphate utilization. The proteomes provide a detailed view of enzymes involved in central carbon and nitrogen metabolism. Trends in protein expression over the time courses were deduced from a protein abundance index, which also revealed the importance of stress pathway proteins in both cultures. As expected, the ΔphoP mutant was deficient in expression of PhoP-dependent genes, and several putatively compensatory metabolic and regulatory pathways for phosphate scavenging were detected. Notably there is a succession of switches that coordinately induce the production of enzymes for five different secondary metabolite biosynthesis pathways over the course of the batch cultures.
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2.90Impact points
The PII protein GlnK is a pleiotropic regulator for morphological differentiation and secondary metabolism in Streptomyces coelicolor.
Applied microbiology and biotechnology. 12/2011; 92(6):1219-36.
GlnK is an important nitrogen sensor protein in Streptomyces coelicolor. Deletion of glnK results in a medium-dependent failure of aerial mycelium and spore formation and loss of antibiotic production. Thus, GlnK is not only a regulator of nitrogen metabolism but also of morphological differentiatio... [more] GlnK is an important nitrogen sensor protein in Streptomyces coelicolor. Deletion of glnK results in a medium-dependent failure of aerial mycelium and spore formation and loss of antibiotic production. Thus, GlnK is not only a regulator of nitrogen metabolism but also of morphological differentiation and secondary metabolite production. Through a comparative transcriptomic approach between the S. coelicolor wild-type and a S. coelicolor glnK mutant strain, 142 genes were identified that are differentially regulated in both strains. Among these are genes of the ram and rag operon, which are involved in S. coelicolor morphogenesis, as well as genes involved in gas vesicle biosynthesis and ectoine biosynthesis. Surprisingly, no relevant nitrogen genes were found to be differentially regulated, revealing that GlnK is not an important nitrogen sensor under the tested conditions.
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4.93Impact points
Identifying associations between amino acid changes and meta information in alignments.
Bioinformatics (Oxford, England). 08/2011; 27(20):2782-9.
We present a method that identifies associations between amino acid changes in potentially significant sites in an alignment (taking into account several amino acid properties) with phenotypic data, through the phylogenetic mixed model. The latter accounts for the dependency of the observations (org... [more] We present a method that identifies associations between amino acid changes in potentially significant sites in an alignment (taking into account several amino acid properties) with phenotypic data, through the phylogenetic mixed model. The latter accounts for the dependency of the observations (organisms). It is known from previous studies that the pathogenic aspect of many organisms may be associated with a single or just few changes in amino acids, which have a strong structural and/or functional impact on the protein. Discovering these sites is a big step toward understanding pathogenicity. Our method is able to discover such sites in proteins responsible for the pathogenic character of a group of bacteria. We use our method to predict potentially significant sites in the RpoS protein from a set of 209 bacteria. Several sites with significant differences in biological relevant regions were found. Our tool is publicly available on the CRAN network at http://cran.r-project.org/ naya@pasteur.edu.uy Supplementary data are available at Bioinformatics online.
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4.93Impact points
GaggleBridge: collaborative data analysis.
Bioinformatics (Oxford, England). 07/2011; 27(18):2612-3.
Tools aiding in collaborative data analysis are becoming ever more important as researchers work together over long distances. We present an extension to the Gaggle framework, which has been widely adopted as a tool to enable data exchange between different analysis programs on one computer. Our pro... [more] Tools aiding in collaborative data analysis are becoming ever more important as researchers work together over long distances. We present an extension to the Gaggle framework, which has been widely adopted as a tool to enable data exchange between different analysis programs on one computer. Our program, GaggleBridge, transparently extends this functionality to allow data exchange between Gaggle users at different geographic locations using network communication. GaggleBridge can automatically set up SSH tunnels to traverse firewalls while adding some security features to the Gaggle communication. GaggleBridge is available as open-source software implemented in the Java language at http://it.inf.uni-tuebingen.de/gb. florian.battke@uni-tuebingen.de Supplementary data are available at Bioinformatics online.
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4.93Impact points
MGV: a generic graph viewer for comparative omics data.
Bioinformatics (Oxford, England). 06/2011; 27(16):2248-55.
High-throughput transcriptomics, proteomics and metabolomics methods have revolutionized our knowledge of biological systems. To gain knowledge from comparative omics studies, strong data integration and visualization features are required. Knowledge gained from these studies is often available in t... [more] High-throughput transcriptomics, proteomics and metabolomics methods have revolutionized our knowledge of biological systems. To gain knowledge from comparative omics studies, strong data integration and visualization features are required. Knowledge gained from these studies is often available in the form of graphs, and their visualization is especially useful in a wide range of systems biology topics, including pathway analysis, interaction networks or gene models. Especially, it is necessary to compare biological models with measured data. This allows the identification of new models and new insights into existing ones. We present MGV, a versatile generic graph viewer for multiomics data. MGV is integrated into Mayday (Battke et al., 2010). It extends Mayday's visual analytics capabilities by integrating a wide range of biological models, high-throughput data and meta information to display enriched graphs that combine data and models. A wide range of tools is available for visualization of nodes, data-aware graph layout as well as automatic and manual aggregation and refinement of the data. We show the usefulness of MGV applied to several problems, including differential expression of alternative transcripts, transcription factor interaction, cross-study clustering comparison and integration of transcriptomics and metabolomics data for pathway analysis. MGV is a open-source software implemented in Java and freely available as a part of Mayday at www.microarray-analysis.org/mayday. symons@informatik.uni-tuebingen.de Supplementary data are available at Bioinformatics online.
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Deletion of the signalling molecule synthase ScbA has pleiotropic effects on secondary metabolite biosynthesis, morphological differentiation and primary metabolism in Streptomyces coelicolor A3(2).
Microbial biotechnology. 03/2011; 4(2):239-51.
Streptomycetes have high biotechnological relevance as producers of diverse metabolites widely used in medical and agricultural applications. The biosynthesis of these metabolites is controlled by signalling molecules, γ-butyrolactones, that act as bacterial hormones. In Streptomyces coelicolor, a g... [more] Streptomycetes have high biotechnological relevance as producers of diverse metabolites widely used in medical and agricultural applications. The biosynthesis of these metabolites is controlled by signalling molecules, γ-butyrolactones, that act as bacterial hormones. In Streptomyces coelicolor, a group of signalling molecules called SCBs (S. coelicolorbutanolides) regulates production of the pigmented antibiotics coelicolor polyketide (CPK), actinorhodin and undecylprodigiosin. The γ-butyrolactone synthase ScbA is responsible for the biosynthesis of SCBs. Here we show the results of a genome-wide transcriptome analysis of a scbA deletion mutant prior to and during the transition to antibiotic production. We report a strong perturbation in the expression of three pigmented antibiotic clusters in the mutant throughout the growth curve, thus providing a molecular explanation for the antibiotic phenotype observed previously. Our study also revealed, for the first time, that the secondary metabolite cluster responsible for synthesis of the siderophore desferrioxamine is under the control of SCB signalling. Moreover, expression of the genes encoding enzymes for primary metabolism pathways, which supply antibiotic precursors and genes for morphological differentiation, was found shifted earlier in time in the mutant. In conclusion, our time series analysis demonstrates new details of the regulatory effects of the γ-butyrolactone system in Streptomyces.
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2.02Impact points
A technical platform for generating reproducible expression data from Streptomyces coelicolor batch cultivations.
Advances in experimental medicine and biology. 01/2011; 696:3-15.
Streptomyces coelicolor, the model species of the genus Streptomyces, presents a complex life cycle of successive morphological and biochemical changes involving the formation of substrate and aerial mycelium, sporulation and the production of antibiotics. The switch from primary to secondary metabo... [more] Streptomyces coelicolor, the model species of the genus Streptomyces, presents a complex life cycle of successive morphological and biochemical changes involving the formation of substrate and aerial mycelium, sporulation and the production of antibiotics. The switch from primary to secondary metabolism can be triggered by nutrient starvation and is of particular interest as some of the secondary metabolites produced by related Streptomycetes are commercially relevant. To understand these events on a molecular basis, a reliable technical platform encompassing reproducible fermentation as well as generation of coherent transcriptomic data is required. Here, we investigate the technical basis of a previous study as reported by Nieselt et al. (BMC Genomics 11:10, 2010) in more detail, based on the same samples and focusing on the validation of the custom-designed microarray as well as on the reproducibility of the data generated from biological replicates. We show that the protocols developed result in highly coherent transcriptomic measurements. Furthermore, we use the data to predict chromosomal gene clusters, extending previously known clusters as well as predicting interesting new clusters with consistent functional annotations.
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Identifying associations between amino acid changes and meta information in alignments.
Bioinformatics. 01/2011; 27:2782-2789.
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3.43Impact points
nocoRNAc: characterization of non-coding RNAs in prokaryotes.
BMC bioinformatics. 01/2011; 12:40.
The interest in non-coding RNAs (ncRNAs) constantly rose during the past few years because of the wide spectrum of biological processes in which they are involved. This led to the discovery of numerous ncRNA genes across many species. However, for most organisms the non-coding transcriptome still re... [more] The interest in non-coding RNAs (ncRNAs) constantly rose during the past few years because of the wide spectrum of biological processes in which they are involved. This led to the discovery of numerous ncRNA genes across many species. However, for most organisms the non-coding transcriptome still remains unexplored to a great extent. Various experimental techniques for the identification of ncRNA transcripts are available, but as these methods are costly and time-consuming, there is a need for computational methods that allow the detection of functional RNAs in complete genomes in order to suggest elements for further experiments. Several programs for the genome-wide prediction of functional RNAs have been developed but most of them predict a genomic locus with no indication whether the element is transcribed or not. We present NOCORNAc, a program for the genome-wide prediction of ncRNA transcripts in bacteria. NOCORNAc incorporates various procedures for the detection of transcriptional features which are then integrated with functional ncRNA loci to determine the transcript coordinates. We applied RNAz and NOCORNAc to the genome of Streptomyces coelicolor and detected more than 800 putative ncRNA transcripts most of them located antisense to protein-coding regions. Using a custom design microarray we profiled the expression of about 400 of these elements and found more than 300 to be transcribed, 38 of them are predicted novel ncRNA genes in intergenic regions. The expression patterns of many ncRNAs are similarly complex as those of the protein-coding genes, in particular many antisense ncRNAs show a high expression correlation with their protein-coding partner. We have developed NOCORNAc, a framework that facilitates the automated characterization of functional ncRNAs. NOCORNAc increases the confidence of predicted ncRNA loci, especially if they contain transcribed ncRNAs. NOCORNAc is not restricted to intergenic regions, but it is applicable to the prediction of ncRNA transcripts in whole microbial genomes. The software as well as a user guide and example data is available at http://www.zbit.uni-tuebingen.de/pas/nocornac.htm.
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4.41Impact points
Mayday SeaSight: combined analysis of deep sequencing and microarray data.
PloS one. 01/2011; 6(1):e16345.
Recently emerged deep sequencing technologies offer new high-throughput methods to quantify gene expression, epigenetic modifications and DNA-protein binding. From a computational point of view, the data is very different from that produced by the already established microarray technology, providing... [more] Recently emerged deep sequencing technologies offer new high-throughput methods to quantify gene expression, epigenetic modifications and DNA-protein binding. From a computational point of view, the data is very different from that produced by the already established microarray technology, providing a new perspective on the samples under study and complementing microarray gene expression data. Software offering the integrated analysis of data from different technologies is of growing importance as new data emerge in systems biology studies. Mayday is an extensible platform for visual data exploration and interactive analysis and provides many methods for dissecting complex transcriptome datasets. We present Mayday SeaSight, an extension that allows to integrate data from different platforms such as deep sequencing and microarrays. It offers methods for computing expression values from mapped reads and raw microarray data, background correction and normalization and linking microarray probes to genomic coordinates. It is now possible to use Mayday's wealth of methods to analyze sequencing data and to combine data from different technologies in one analysis.
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3.43Impact points
Mayday--integrative analytics for expression data.
BMC bioinformatics. 03/2010; 11:121.
DNA Microarrays have become the standard method for large scale analyses of gene expression and epigenomics. The increasing complexity and inherent noisiness of the generated data makes visual data exploration ever more important. Fast deployment of new methods as well as a combination of predefined... [more] DNA Microarrays have become the standard method for large scale analyses of gene expression and epigenomics. The increasing complexity and inherent noisiness of the generated data makes visual data exploration ever more important. Fast deployment of new methods as well as a combination of predefined, easy to apply methods with programmer's access to the data are important requirements for any analysis framework. Mayday is an open source platform with emphasis on visual data exploration and analysis. Many built-in methods for clustering, machine learning and classification are provided for dissecting complex datasets. Plugins can easily be written to extend Mayday's functionality in a large number of ways. As Java program, Mayday is platform-independent and can be used as Java WebStart application without any installation. Mayday can import data from several file formats, database connectivity is included for efficient data organization. Numerous interactive visualization tools, including box plots, profile plots, principal component plots and a heatmap are available, can be enhanced with metadata and exported as publication quality vector files. We have rewritten large parts of Mayday's core to make it more efficient and ready for future developments. Among the large number of new plugins are an automated processing framework, dynamic filtering, new and efficient clustering methods, a machine learning module and database connectivity. Extensive manual data analysis can be done using an inbuilt R terminal and an integrated SQL querying interface. Our visualization framework has become more powerful, new plot types have been added and existing plots improved. We present a major extension of Mayday, a very versatile open-source framework for efficient micro array data analysis designed for biologists and bioinformaticians. Most everyday tasks are already covered. The large number of available plugins as well as the extension possibilities using compiled plugins and ad-hoc scripting allow for the rapid adaption of Mayday also to very specialized data exploration. Mayday is available at http://microarray-analysis.org.
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Efficient Sequence Clustering for RNA-Seq Data without a Reference Genome.
German Conference on Bioinformatics 2010, September 20-22, 2010, Technische Universität Carolo Wilhelmina zu Braunschweig, Germany; 01/2010
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3.56Impact points
Circadian expression of clock- and tumor suppressor genes in human oral mucosa.
Cellular physiology and biochemistry : international journal of experimental cellular physiology, biochemistry, and pharmacology. 01/2010; 26(2):155-66.
Circadian rhythms are daily oscillations of multiple biological processes driven by endogenous clocks. Imbalance of these rhythms has been associated with cancerogenesis in humans. To further elucidate the role circadian clocks have in cellular growth control, tumor suppression and cancer treatment,... [more] Circadian rhythms are daily oscillations of multiple biological processes driven by endogenous clocks. Imbalance of these rhythms has been associated with cancerogenesis in humans. To further elucidate the role circadian clocks have in cellular growth control, tumor suppression and cancer treatment, it is revealing to know how clock genes and clock-controlled genes are regulated in healthy humans. Therefore comparative microarray analyses were conducted investigating the relative mRNA expression of clock genes throughout a 24-hour period in cell samples obtained from oral mucosa of eight healthy diurnally active male study participants. Differentially expressed selected genes of interest were additionally evaluated using qRT-PCR. Microarray analysis revealed 33 significant differentially regulated clock genes and clock- controlled genes, throughout a one day period (6.00h, 12.00h, 18.00h, 24.00h). Hereof were 16 clock genes and 17 clock- controlled genes including tumor suppressor- and oncogenes. qRT-PCR of selected genes of interest, such as hPER2, hCRY1, hBMAL1, hCCRN4L and hSMAD5 revealed significant circadian regulations. Our study revealed a proper circadian regulation profile of several clock- and tumor suppressor genes at defined points in time in the participants studied. These findings could provide important information regarding genes displaying the same expression profile in the gastrointestinal tract amounting to a physiological expression profile of healthy humans. In the future asynchronous regulations of those genes might be an additional assistant method to detect derivations distinguishing normal from malignant tissue or assessing risk factors for cancer.
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3.56Impact points
Phosphoglycerate kinase 1 promoting tumor progression and metastasis in gastric cancer - detected in a tumor mouse model using positron emission tomography/magnetic resonance imaging.
Cellular physiology and biochemistry : international journal of experimental cellular physiology, biochemistry, and pharmacology. 01/2010; 26(2):147-54.
Tumor dissemination is frequent in gastric cancer and implies a poor prognosis. Cure is only achievable provided an accurate staging is performed at primary diagnosis. In previous studies we were able to show a relevant impact of increased phosphoglycerate kinase 1 expression (PGK1; a glycolytic enz... [more] Tumor dissemination is frequent in gastric cancer and implies a poor prognosis. Cure is only achievable provided an accurate staging is performed at primary diagnosis. In previous studies we were able to show a relevant impact of increased phosphoglycerate kinase 1 expression (PGK1; a glycolytic enzyme) on invasive properties of gastric cancer in-vivo and in-vitro. Thus the aim of the present study was to evaluate the effect of enhanced PGK1 expression in gastric cancer employing magnetic resonance (MR)-imaging combined with positron emission tomography (PET), a recently emerging new high resolution imaging technique in a mouse model. A metastatic nude mouse model simulating human gastric cancer behavior by orthotopic tumor implantation was established. Mice were divided into one control group (n=5) and two experimental groups (n=30) divided by half in animals baring tumors from MKN45-cells and MKN45-cells with plasmid-mediated overexpression of PGK1. In the course of tumor growth MR-imaging and PET/MRI fusion was performed. Successively experimental animals were examined macroscopically and histopathologically regarding growth, metastasis and PGK1 expression. Elevated PGK1 expression increased invasive and metastatic behavior of implanted gastric tumors significantly. MR/PET- imaging results in-vivoand subsequent ex-vivo findings concerning tumor growth and metastasis correlated excellently and could be underlined by concordant immuohistochemical PGK1 staining. Consistent in-vivo findings suggest that PGK1 might be crucially involved in gastric malignancy regarding growth and metastasis, which was also underlined by novel imaging techniques. Thus, PGK1 may be exploited as a prognostic marker and/or be of potential therapeutic value preventing malignant dissemination.
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Integrative systems biology visualization with MAYDAY.
Journal of integrative bioinformatics. 01/2010; 7(3).
Visualization is pivotal for gaining insight in systems biology data. As the size and complexity of datasets and supplemental information increases, an efficient, integrated framework for general and specialized views is necessary. MAYDAY is an application for analysis and visualization of general &... [more] Visualization is pivotal for gaining insight in systems biology data. As the size and complexity of datasets and supplemental information increases, an efficient, integrated framework for general and specialized views is necessary. MAYDAY is an application for analysis and visualization of general 'omics' data. It follows a trifold approach for data visualization, consisting of flexible data preprocessing, highly customizable data perspective plots for general purpose visualization and systems based plots. Here, we introduce two new systems biology visualization tools for MAYDAY. Efficiently implemented genomic viewers allow the display of variables associated with genomic locations. Multiple variables can be viewed using our new track-based ChromeTracks tool. A functional perspective is provided by visualizing metabolic pathways either in KEGG or BioPax format. Multiple options of displaying pathway components are available, including Systems Biology Graphical Notation (SBGN) glyphs. Furthermore, pathways can be viewed together with gene expression data either as heatmaps or profiles. We apply our tools to two 'omics' datasets of Pseudomonas aeruginosa. The general analysis and visualization tools of MAYDAY as well as our ChromeTracks viewer are applied to a transcriptome dataset. We furthermore integrate this dataset with a metabolome dataset and compare the activity of amino acid degradation pathways between these two datasets, by visually enhancing the pathway diagrams produced by MAYDAY.
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3.76Impact points
The dynamic architecture of the metabolic switch in Streptomyces coelicolor.
BMC genomics. 01/2010; 11:10.
During the lifetime of a fermenter culture, the soil bacterium S. coelicolor undergoes a major metabolic switch from exponential growth to antibiotic production. We have studied gene expression patterns during this switch, using a specifically designed Affymetrix genechip and a high-resolution time-... [more] During the lifetime of a fermenter culture, the soil bacterium S. coelicolor undergoes a major metabolic switch from exponential growth to antibiotic production. We have studied gene expression patterns during this switch, using a specifically designed Affymetrix genechip and a high-resolution time-series of fermenter-grown samples. Surprisingly, we find that the metabolic switch actually consists of multiple finely orchestrated switching events. Strongly coherent clusters of genes show drastic changes in gene expression already many hours before the classically defined transition phase where the switch from primary to secondary metabolism was expected. The main switch in gene expression takes only 2 hours, and changes in antibiotic biosynthesis genes are delayed relative to the metabolic rearrangements. Furthermore, global variation in morphogenesis genes indicates an involvement of cell differentiation pathways in the decision phase leading up to the commitment to antibiotic biosynthesis. Our study provides the first detailed insights into the complex sequence of early regulatory events during and preceding the major metabolic switch in S. coelicolor, which will form the starting point for future attempts at engineering antibiotic production in a biotechnological setting.
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3.94Impact points
Non-coding RNA of glutamine synthetase I modulates antibiotic production in Streptomyces coelicolor A3(2).
Journal of bacteriology. 12/2009;
Overexpression of antisense chromosomal cis-encoded non-coding RNA (ncRNA) in glutamine synthetase I resulted in decrease of growth, protein synthesis and antibiotic production in Streptomyces coelicolor. Additionally, we predicted 3597 cis-encoded ncRNAs and validated 13 of them experimentally, inc... [more] Overexpression of antisense chromosomal cis-encoded non-coding RNA (ncRNA) in glutamine synthetase I resulted in decrease of growth, protein synthesis and antibiotic production in Streptomyces coelicolor. Additionally, we predicted 3597 cis-encoded ncRNAs and validated 13 of them experimentally, including several ncRNAs that are differentially expressed in bacterial hormone defective mutants.
Following (7)
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Peter R Wills
University of Auckland -
Florian Battke
Eberhard-Karls-Universität Tübingen -
Alexander Wentzel
Stiftelsen for industriell og teknisk forskning -
Till Albrecht
Frutarom Savory Solutions -
Jochen Gaedcke
Georg-August-Universität Göttingen
