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Heidelberg, Germany

Sipos B.,European Bioinformatics Institute | Massingham T.,European Bioinformatics Institute | Stutz A.M.,Genome Biology Research Unit | Goldman N.,European Bioinformatics Institute

The rise of Next Generation Sequencing (NGS) technologies has transformed de novo genome sequencing into an accessible research tool, but obtaining high quality eukaryotic genome assemblies remains a challenge, mostly due to the abundance of repetitive elements. These also make it difficult to study nucleotide polymorphism in repetitive regions, including certain types of structural variations. One solution proposed for resolving such regions is Sequence Assembly aided by Mutagenesis (SAM), which relies on the fact that introducing enough random mutations breaks the repetitive structure, making assembly possible. Sequencing many different mutated copies permits the sequence of the repetitive region to be inferred by consensus methods. However, this approach relies on molecular cloning in order to isolate and amplify individual mutant copies, making it hard to scale-up the approach for use in conjunction with high-throughput sequencing technologies. To address this problem, we propose NG-SAM, a modified version of the SAM protocol that relies on PCR and dilution steps only, coupled to a NGS workflow. NG-SAM therefore has the potential to be scaled-up, e.g. using emerging microfluidics technologies. We built a realistic simulation pipeline to study the feasibility of NG-SAM, and our results suggest that under appropriate experimental conditions the approach might be successfully put into practice. Moreover, our simulations suggest that NG-SAM is capable of reconstructing robustly a wide range of potential target sequences of varying lengths and repetitive structures. © 2012 Sipos et al. Source

Phelan V.V.,University of California at San Diego | Moree W.J.,University of California at San Diego | Aguilar J.,University of California at San Diego | Cornett D.S.,Bruker | And 6 more authors.
Journal of Bacteriology

In microbiology, gene disruption and subsequent experiments often center on phenotypic changes caused by one class of specialized metabolites (quorum sensors, virulence factors, or natural products), disregarding global downstream metabolic effects. With the recent development of mass spectrometry-based methods and technologies for microbial metabolomics investigations, it is now possible to visualize global production of diverse classes of microbial specialized metabolites simultaneously. Using imaging mass spectrometry (IMS) applied to the analysis of microbiology experiments, we can observe the effects of mutations, knockouts, insertions, and complementation on the interactive metabolome. In this study, a combination of IMS and liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to visualize the impact on specialized metabolite production of a transposon insertion into a Pseudomonas aeruginosa phenazine biosynthetic gene, phzF2. The disruption of phenazine biosynthesis led to broad changes in specialized metabolite production, including loss of pyoverdine production. This shift in specialized metabolite production significantly alters the metabolic outcome of an interaction with Aspergillus fumigatus by influencing triacetylfusarinine production. © 2014, American Society for Microbiology. Source

Rasche F.,Friedrich - Schiller University of Jena | Scheubert K.,Friedrich - Schiller University of Jena | Hufsky F.,Friedrich - Schiller University of Jena | Hufsky F.,Max Planck Institute for Chemical Ecology | And 4 more authors.
Analytical Chemistry

Mass spectrometry allows sensitive, automated, and high-throughput analysis of small molecules. In principle, tandem mass spectrometry allows us to identify "unknown" small molecules not in any database, but the automated interpretation of such data is in its infancy. Fragmentation trees have recently been introduced for the automated analysis of the fragmentation patterns of small molecules. We present a method for the automated comparison of such fragmentation patterns, based on aligning the compounds' fragmentation trees. We cluster compounds based solely on their fragmentation patterns and show a good agreement with known compound classes. Fragmentation pattern similarities are strongly correlated with the chemical similarity of molecules. We present a tool for searching a database for compounds with fragmentation pattern similar to an unknown sample compound. We apply this tool to metabolites from Icelandic poppy. Our method allows fully automated computational identification of small molecules that cannot be found in any database. © 2012 American Chemical Society. Source

Richter J.,University of Kiel | Schlesner M.,German Cancer Research Center | Hoffmann S.,University of Leipzig | Kreuz M.,University of Leipzig | And 55 more authors.
Nature Genetics

Burkitt lymphoma is a mature aggressive B-cell lymphoma derived from germinal center B cells. Its cytogenetic hallmark is the Burkitt translocation t(8;14)(q24;q32) and its variants, which juxtapose the MYC oncogene with one of the three immunoglobulin loci. Consequently, MYC is deregulated, resulting in massive perturbation of gene expression. Nevertheless, MYC deregulation alone seems not to be sufficient to drive Burkitt lymphomagenesis. By whole-genome, whole-exome and transcriptome sequencing of four prototypical Burkitt lymphomas with immunoglobulin gene (IG)-MYC translocation, we identified seven recurrently mutated genes. One of these genes, ID3, mapped to a region of focal homozygous loss in Burkitt lymphoma. In an extended cohort, 36 of 53 molecularly defined Burkitt lymphomas (68%) carried potentially damaging mutations of ID3. These were strongly enriched at somatic hypermutation motifs. Only 6 of 47 other B-cell lymphomas with the IG-MYC translocation (13%) carried ID3 mutations. These findings suggest that cooperation between ID3 inactivation and IG-MYC translocation is a hallmark of Burkitt lymphomagenesis. © 2012 Nature America, Inc. All rights reserved. Source

The ability to sequence entire individual human genomes has heralded a new era in human genetics. Such advances in sequencing technologies make it possible to address new questions such as the generation of a comprehensive map of common and rare genetic variants in humans. The 1000 Genome Project will analyze 2500 genomes and is expected to greatly expand our knowledge about genomic variation, both on single nucleotide polymorphisms and genomic structural variants in a number of human ethnic populations. Furthermore, the possibility to use these new sequencing technologies for such large scale projects will be evaluated. Finally, new bioinformatics solutions will be developed to efficiently store and process such large volumes of data for the scientific community. This catalogue of common and rare variations will facilitate the development of better methods for phenotype-genotype associations and help uncover the molecular bases for a variety of diseases in the near future. © 2010 Springer-Verlag. Source

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