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Aiche S.,Free University of Berlin | Aiche S.,International Max Planck Research School for Computational Biology and Scientific Computing | Reinert K.,Free University of Berlin | Schutte C.,Free University of Berlin | And 3 more authors.
PLoS ONE | Year: 2012

Background: Proteases play an essential part in a variety of biological processes. Besides their importance under healthy conditions they are also known to have a crucial role in complex diseases like cancer. In recent years, it has been shown that not only the fragments produced by proteases but also their dynamics, especially ex vivo, can serve as biomarkers. But so far, only a few approaches were taken to explicitly model the dynamics of proteolysis in the context of mass spectrometry. Results: We introduce a new concept to model proteolytic processes, the degradation graph. The degradation graph is an extension of the cleavage graph, a data structure to reconstruct and visualize the proteolytic process. In contrast to previous approaches we extended the model to incorporate endoproteolytic processes and present a method to construct a degradation graph from mass spectrometry time series data. Based on a degradation graph and the intensities extracted from the mass spectra it is possible to estimate reaction rates of the underlying processes. We further suggest a score to rate different degradation graphs in their ability to explain the observed data. This score is used in an iterative heuristic to improve the structure of the initially constructed degradation graph. Conclusion: We show that the proposed method is able to recover all degraded and generated peptides, the underlying reactions, and the reaction rates of proteolytic processes based on mass spectrometry time series data. We use simulated and real data to demonstrate that a given process can be reconstructed even in the presence of extensive noise, isobaric signals and false identifications. While the model is currently only validated on peptide data it is also applicable to proteins, as long as the necessary time series data can be produced. © 2012 Aiche et al. Source


Andreotti S.,Free University of Berlin | Andreotti S.,International Max Planck Research School for Computational Biology and Scientific Computing | Reinert K.,Free University of Berlin | Canzar S.,Johns Hopkins University
Journal of Computational Biology | Year: 2013

The reconstruction of the history of evolutionary genome-wide events among a set of related organisms is of great biological interest since it can help to reveal the genomic basis of phenotypes. The sequencing of whole genomes faciliates the study of gene families that vary in size through duplication and loss events, like transfer RNA. However, a high sequence similarity often does not allow one to distinguish between orthologs and paralogs. Previous methods have addressed this difficulty by taking into account flanking regions of members of a family independently. We go one step further by inferring the order of genes of (a set of) families for ancestral genomes by considering the order of these genes on sequenced genomes. We present a novel branch-and-cut algorithm to solve the two species small phylogeny problem in the evolutionary model of duplications and losses. On average, our implementation, DupLoCut, improves the running time of a recently proposed method in the experiments on six Vibrionaceae lineages by a factor of ∼200. Besides the mere improvement in running time, the efficiency of our approach allows us to extend our model from cherries of a species tree, that is, subtrees with two leaves, to the median of three species setting. Being able to determine the median of three species is of key importance to one of the most common approaches to ancestral reconstruction, and our experiments show that its repeated computation considerably reduces the number of duplications and losses along the tree both on simulated instances comprising 128 leaves and a set of Bacillus genomes. Furthermore, in our simulations we show that a reduction in cost goes hand in hand with an improvement of the predicted ancestral genomes. Finally, we prove that the small phylogeny problem in the duplication-loss model is NP-complete already for two species. © Copyright 2013, Mary Ann Liebert, Inc. Source


Lei H.,Charite - Medical University of Berlin | Kuchenbecker L.,Charite - Medical University of Berlin | Kuchenbecker L.,International Max Planck Research School for Computational Biology and Scientific Computing | Streitz M.,Charite - Medical University of Berlin | And 11 more authors.
American Journal of Transplantation | Year: 2015

Adoptive immunotherapy with regulatory T cells (Treg) is a new option to promote immune tolerance following solid organ transplantation (SOT). However, Treg from elderly patients awaiting transplantation are dominated by the CD45RA-CD62L+ central memory type Treg subset (TregCM), and the yield of well-characterized and stable naïve Treg (TregN) is low. It is, therefore, important to determine whether these TregCM are derived from the thymus and express high stability, suppressive capacity and a broad antigen repertoire like TregN. In this study, we showed that TregCM use a different T cell receptor (TCR) repertoire from conventional T cells (Tconv), using next-generation sequencing of all 24 Vβ families, with an average depth of 534 677 sequences. This showed almost no contamination with induced Treg. Furthermore, TregCM showed enhanced suppressive activity on Tconv at early checkpoints of immune activation controlling activation markers expression and cytokine secretion, but comparable inhibition of proliferation. Following in vitro expansion under mTOR inhibition, TregCM expanded equally as well as TregN without losing their function. Despite relatively limited TCR repertoire, TregCM also showed specific alloresponse, although slightly reduced compared to TregN. These results support the therapeutic usefulness of manufacturing Treg products from CD45RA-CD62L+ Treg-enriched starting material to be applied for adoptive Treg therapy. © Copyright 2015 The American Society of Transplantation and the American Society of Transplant Surgeons. Source


Richard H.,Max Planck Institute for Molecular Genetics | Schulz M.H.,Max Planck Institute for Molecular Genetics | Schulz M.H.,International Max Planck Research School for Computational Biology and Scientific Computing | Sultan M.,Max Planck Institute for Molecular Genetics | And 9 more authors.
Nucleic Acids Research | Year: 2010

Alternative splicing, polyadenylation of premessenger RNA molecules and differential promoter usage can produce a variety of transcript isoforms whose respective expression levels are regulated in time and space, thus contributing specific biological functions. However, the repertoire of mammalian alternative transcripts and their regulation are still poorly understood. Second-generation sequencing is now opening unprecedented routes to address the analysis of entire transcriptomes. Here, we developed methods that allow the prediction and quantification of alternative isoforms derived solely from exon expression levels in RNA-Seq data. These are based on an explicit statistical model and enable the prediction of alternative isoforms within or between conditions using any known gene annotation, as well as the relative quantification of known transcript structures. Applying these methods to a human RNA-Seq dataset, we validated a significant fraction of the predictions by RT-PCR. Data further showed that these predictions correlated well with information originating from junction reads. A direct comparison with exon arrays indicated improved performances of RNA-Seq over microarrays in the prediction of skipped exons. Altogether, the set of methods presented here comprehensively addresses multiple aspects of alternative isoform analysis. The software is available as an open-source R-package called Solas at http://cmb.molgen.mpg.de/2ndGenerationSequencing/Solas/. © The Author(s) 2010. Published by Oxford University Press. Source


Dziubianau M.,Charite - Medical University of Berlin | Hecht J.,Charite - Medical University of Berlin | Hecht J.,Max Planck Institute for Molecular Genetics | Kuchenbecker L.,Charite - Medical University of Berlin | And 15 more authors.
American Journal of Transplantation | Year: 2013

Clonotype analysis is essential for complete characterization of antigen-specific T cells. Moreover, knowledge on clonal identity allows tracking of antigen-specific T cells in whole blood and tissue infiltrates and can provide information on antigenic specificity. Here, we developed a next generation sequencing (NGS)-based platform for the highly quantitative clonotype characterization of T cells and determined requirements for the unbiased characterization of the input material (DNA, RNA, ex vivo derived or cell culture expanded T cells). Thereafter we performed T cell receptor (TCR) repertoire analysis of various specimens in clinical settings including cytomegalovirus (CMV), polyomavirus BK (BKV) reactivation and acute cellular allograft rejection. Our results revealed dynamic nature of virus-specific T cell clonotypes; CMV reactivation was linked to appearance of new highly abundant antigen-specific clonalities. Moreover, analysis of clonotype overlap between BKV-, alloantigen-specific T cell-, kidney allograft- and urine-derived lymphocytes provided hints for the differential diagnosis of allograft dysfunction and enabled appropriate therapy adjustment. We believe that the established approach will provide insights into the regulation of virus-specific/anti-tumor immunity and has high diagnostic potential in the clinical routine. © Copyright 2013 The American Society of Transplantation and the American Society of Transplant Surgeons. Source

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