Netherlands Institute for Systems Biology NISB

Amsterdam, Netherlands

Netherlands Institute for Systems Biology NISB

Amsterdam, Netherlands
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Andreotti S.,Free University of Berlin | Klau G.W.,International Max Planck Research School for Computational Biology and Scientific Computing | Reinert K.,Life science Group | Reinert K.,Netherlands Institute for Systems Biology NISB
IEEE/ACM Transactions on Computational Biology and Bioinformatics | Year: 2012

Peptide sequencing from mass spectrometry data is a key step in proteome research. Especially de novo sequencing, the identification of a peptide from its spectrum alone, is still a challenge even for state-of-the-art algorithmic approaches. In this paper, we present antilope, a new fast and flexible approach based on mathematical programming. It builds on the spectrum graph model and works with a variety of scoring schemes. antilope combines Lagrangian relaxation for solving an integer linear programming formulation with an adaptation of Yen's k shortest paths algorithm. It shows a significant improvement in running time compared to mixed integer optimization and performs at the same speed like other state-of-the-art tools. We also implemented a generic probabilistic scoring scheme that can be trained automatically for a data set of annotated spectra and is independent of the mass spectrometer type. Evaluations on benchmark data show that antilope is competitive to the popular state-of-the-art programs PepNovo and NovoHMM both in terms of runtime and accuracy. Furthermore, it offers increased flexibility in the number of considered ion types. antilope will be freely available as part of the open source proteomics library OpenMS. © 2006 IEEE.

Brul S.,Netherlands Institute for Systems Biology NISB | van Beilen J.,Netherlands Institute for Systems Biology NISB | Caspers M.,TNO | O'Brien A.,Netherlands Institute for Systems Biology NISB | And 5 more authors.
Food Microbiology | Year: 2011

Bacterial spore formers are prime organisms of concern in the food industry. Spores from the genus Bacillus are extremely stress resistant, most notably exemplified by high thermotolerance. This sometimes allows surviving spores to germinate and grow out to vegetative cells causing food spoilage and possible intoxication. Similar issues though more pending toward spore toxigenicity are observed for the anaerobic Clostridia. The paper indicates the nature of stress resistance and highlights contemporary molecular approaches to analyze the mechanistic basis of it in Bacilli. A molecular comparison between a laboratory strain and a food borne isolate, very similar at the genomic level to the laboratory strain but generating extremely heat resistant spores, is discussed. The approaches cover genome-wide genotyping, proteomics and genome-wide expression analyses studies. The analyses aim at gathering sufficient molecular information to be able to put together an initial framework for dynamic modelling of spore germination and outgrowth behaviour. Such emerging models should be developed both at the population and at the single spore level. Tools and challenges in achieving the latter are succinctly discussed. © 2010 Elsevier Ltd.

Ter Beek A.,Netherlands Institute for Systems Biology NISB | Wijman J.G.E.,Unilever | Zakrzewska A.,Netherlands Institute for Systems Biology NISB | Orij R.,Netherlands Institute for Systems Biology NISB | And 2 more authors.
Food Microbiology | Year: 2015

The advent of 'omics' techniques bears significant potential for the assessment of the microbiological stability of foods. This requires the integration of molecular data with their implication for cellular physiology. Here we performed a comparative physiological and transcriptional analysis of Bacillus subtilis stressed with three different weak organic acids: the commonly used food preservatives sorbic- and acetic-acid, plus the well-known uncoupler carbonyl cyanide-m-chlorophenyl hydrazone (CCCP). The concentration of each compound needed to cause a similar reduction of the growth rate negatively correlated with their membrane solubility, and positively with the concentration of undissociated acid. Intracellular acidification was demonstrated by expressing a pH-sensitive GFP derivative. The largest drop in intracellular pH was observed in CCCP-stressed cells and was accompanied by the transcriptional induction of the general stress response (GSR) and SigM regulon, responses known to be induced by acidification. The GSR was induced by acetate, but not by sorbate in mildly-stressed cells. Microarray analysis further revealed that all three acids activate transcriptional programs normally seen upon nutrient limitation and cause diverse responses indicative of an adaptation of the cell envelope. Based on the responses observed and the utilized pH measurements, the inhibitory effect of sorbic acid seems to be more focused on the cell membrane than that of acetic acid or CCCP. © 2014 Elsevier Ltd.

Haring M.,University of Amsterdam | Bader R.,University of Amsterdam | Louwers M.,University of Amsterdam | Louwers M.,CropDesign N.V. | And 3 more authors.
Plant Journal | Year: 2010

Paramutation is the transfer of epigenetic information between alleles that leads to a heritable change in expression of one of these alleles. Paramutation at the tissue-specifically expressed maize (Zea mays) b1 locus involves the low-expressing B′ and high-expressing B-I allele. Combined in the same nucleus, B′ heritably changes B-I into B′. A hepta-repeat located 100-kb upstream of the b1 coding region is required for paramutation and for high b1 expression. The role of epigenetic modifications in paramutation is currently not well understood. In this study, we show that the B′ hepta-repeat is DNA-hypermethylated in all tissues analyzed. Importantly, combining B′ and B-I in one nucleus results in de novo methylation of the B-I repeats early in plant development. These findings indicate a role for hepta-repeat DNA methylation in the establishment and maintenance of the silenced B′ state. In contrast, nucleosome occupancy, H3 acetylation, and H3K9 and H3K27 methylation are mainly involved in tissue-specific regulation of the hepta-repeat. Nucleosome depletion and H3 acetylation are tissue-specifically regulated at the B-I hepta-repeat and associated with enhancement of b1 expression. H3K9 and H3K27 methylation are tissue-specifically localized at the B′ hepta-repeat and reinforce the silenced B′ chromatin state. The B′ coding region is H3K27 dimethylated in all tissues analyzed, indicating a role in the maintenance of the silenced B′ state. Taken together, these findings provide insight into the mechanisms underlying paramutation and tissue-specific regulation of b1 at the level of chromatin structure. © 2010 Blackwell Publishing Ltd.

Boele J.,VU University Amsterdam | Boele J.,Netherlands Institute for Systems Biology NISB | Olivier B.G.,VU University Amsterdam | Olivier B.G.,Netherlands Institute for Systems Biology NISB | And 2 more authors.
BMC Systems Biology | Year: 2012

Background: The creation and modification of genome-scale metabolic models is a task that requires specialized software tools. While these are available, subsequently running or visualizing a model often relies on disjoint code, which adds additional actions to the analysis routine and, in our experience, renders these applications suboptimal for routine use by (systems) biologists.Results: The Flux Analysis and Modeling Environment (FAME) is the first web-based modeling tool that combines the tasks of creating, editing, running, and analyzing/visualizing stoichiometric models into a single program. Analysis results can be automatically superimposed on familiar KEGG-like maps. FAME is written in PHP and uses the Python-based PySCeS-CBM for its linear solving capabilities. It comes with a comprehensive manual and a quick-start tutorial, and can be accessed online at With FAME, we present the community with an open source, user-friendly, web-based "one stop shop" for stoichiometric modeling. We expect the application will be of substantial use to investigators and educators alike. © 2012 Boele et al; licensee BioMed Central Ltd.

Schwabe A.,Center for Mathematics and Computer Science | Schwabe A.,Netherlands Institute for Systems Biology NISB | Dobrzynski M.,VU University Amsterdam | Rybakova K.,Netherlands Institute for Systems Biology NISB | And 6 more authors.
Methods in Enzymology | Year: 2011

Quantitative analyses of the dynamics of single cells have become a powerful approach in current cell biology. They give us an unprecedented opportunity to study dynamics of molecular networks at a high level of accuracy in living single cells. Genetically identical cells, growing in the same environment and sharing the same growth history, can differ remarkably in their molecular makeup and physiological behaviors. The origins of this cell-to-cell variability have in many cases been traced to the inevitable stochasticity of molecular reactions. Those mechanisms can cause isogenic cells to have qualitatively different life histories. Many studies indicate that molecular noise can be exploited by cell populations to enhance survival prospects in uncertain environments. On the other hand, cells have evolved noise-suppression mechanisms to cope with the inevitable noise in their functioning so as to reduce the hazardous effects of noise. In this chapter, we discuss key experiments, theoretical results, and physiological consequences of molecular stochasticity to introduce this exciting field to a broader community of (systems) biologists. © 2011 Elsevier Inc. All rights reserved.

Khandelwal R.A.,VU University Amsterdam | Olivier B.G.,VU University Amsterdam | Olivier B.G.,Netherlands Institute for Systems Biology NISB | Roling W.F.M.,VU University Amsterdam | And 5 more authors.
PLoS ONE | Year: 2013

A central focus in studies of microbial communities is the elucidation of the relationships between genotype, phenotype, and dynamic community structure. Here, we present a new computational method called community flux balance analysis (cFBA) to study the metabolic behavior of microbial communities. cFBA integrates the comprehensive metabolic capacities of individual microorganisms in terms of (genome-scale) stoichiometric models of metabolism, and the metabolic interactions between species in the community and abiotic processes. In addition, cFBA considers constraints deriving from reaction stoichiometry, reaction thermodynamics, and the ecosystem. cFBA predicts for communities at balanced growth the maximal community growth rate, the required rates of metabolic reactions within and between microbes and the relative species abundances. In order to predict species abundances and metabolic activities at the optimal community growth rate, a nonlinear optimization problem needs to be solved. We outline the methodology of cFBA and illustrate the approach with two examples of microbial communities. These examples illustrate two useful applications of cFBA. Firstly, cFBA can be used to study how specific biochemical limitations in reaction capacities cause different types of metabolic limitations that microbial consortia can encounter. In silico variations of those maximal capacities allow for a global view of the consortium responses to various metabolic and environmental constraints. Secondly, cFBA is very useful for comparing the performance of different metabolic cross-feeding strategies to either find one that agrees with experimental data or one that is most efficient for the community of microorganisms. © 2013 Khandelwal et al.

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