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PubMed | Universitatsklinikum Heidelberg Heidelberg
Type: | Journal: Frontiers in microbiology | Year: 2015

Pasteurella multocida causes various diseases in a broad range of wild and domestic animals. Toxigenic strains of the serotypes A and D produce an AB protein toxin named Pasteurella multocida toxin (PMT). PMT constitutively activates the heterotrimeric G protein subunits Gq, G13, and Gi through deamidation of a glutamine residue, which results in cytoskeletal rearrangements as well as increased proliferation and survival of the host cell. In human monocytes, PMT alters the lipopolysaccharide (LPS)-induced activation toward a phenotype that suppresses T cell activation. Here we describe that the toxin also modulates CD4-positive T helper (Th) cells directly. PMT amplifies the expansion of Th cells through enhanced cell cycle progression and suppression of apoptosis and manipulates the differentiation of Th subclasses through activation of Signal Transducers and Activators of Transcription (STAT) family members and induction of subtype-specific master transcription factors. A large population of toxin-treated T cells is double-positive for Foxp3 and RORt, the transcription factors expressed by Treg and Th17 cells, respectively. This suggests that these cells could have the potential to turn into Th17 cells or suppressive Treg cells. However, in terms of function, the PMT-differentiated cells behave as inflammatory Th17 cells that produce IL-17 and trigger T cell proliferation.


PubMed | Bielefeld University, Fraunhofer Institute for Algorithms and Scientific Computing, Universitatsklinikum Heidelberg Heidelberg and Justus Liebig University
Type: | Journal: Frontiers in genetics | Year: 2016

Within the recent years clock rates of modern processors stagnated while the demand for computing power continued to grow. This applied particularly for the fields of life sciences and bioinformatics, where new technologies keep on creating rapidly growing piles of raw data with increasing speed. The number of cores per processor increased in an attempt to compensate for slight increments of clock rates. This technological shift demands changes in software development, especially in the field of high performance computing where parallelization techniques are gaining in importance due to the pressing issue of large sized datasets generated by e.g., modern genomics. This paper presents an overview of state-of-the-art manual and automatic acceleration techniques and lists some applications employing these in different areas of sequence informatics. Furthermore, we provide examples for automatic acceleration of two use cases to show typical problems and gains of transforming a serial application to a parallel one. The paper should aid the reader in deciding for a certain techniques for the problem at hand. We compare four different state-of-the-art automatic acceleration approaches (OpenMP, PluTo-SICA, PPCG, and OpenACC). Their performance as well as their applicability for selected use cases is discussed. While optimizations targeting the CPU worked better in the complex k-mer use case, optimizers for Graphics Processing Units (GPUs) performed better in the matrix multiplication example. But performance is only superior at a certain problem size due to data migration overhead. We show that automatic code parallelization is feasible with current compiler software and yields significant increases in execution speed. Automatic optimizers for CPU are mature and usually no additional manual adjustment is required. In contrast, some automatic parallelizers targeting GPUs still lack maturity and are limited to simple statements and structures.


PubMed | Universitatsklinikum Heidelberg Heidelberg
Type: | Journal: Frontiers in neural circuits | Year: 2010

Recent studies using primary neuronal cultures have revealed important roles of the microRNA pathway in the regulation of neuronal development and morphology. For example, miR-134 is involved in dendritogenesis and spine development in hippocampal neurons by regulating local mRNA translation in dendrites. The in vivo roles of microRNAs in these processes are still uninvestigated, partly due to the lack of tools enabling stable in vivo delivery of microRNAs or microRNA inhibitors into neurons of the mammalian brain. Here we describe the construction and validation of a vector-based tool for stable delivery of microRNAs in vivo by use of recombinant adeno-associated virus (rAAV). rAAV-mediated overexpression of miR-134 in neurons of the postnatal mouse brain provided evidence for a negative role of miR-134 in dendritic arborization of cortical layer V pyramidal neurons in vivo, thereby confirming previous findings obtained with cultured neurons. Our system provides researchers with a unique tool to study the role of any candidate microRNA in vivo and can easily be adapted to microRNA loss-of-function studies. This platform should therefore greatly facilitate investigations on the role of microRNAs in synapse development, plasticity and behavior in vivo.

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