TY  - JOUR
A1  - Jahn, Daniel
A1  - Schramm, Sabine
A1  - Schnölzer, Martina
A1  - Heilmann, Clemens J.
A1  - de Koster, Chris G.
A1  - Schütz, Wolfgang
A1  - Benavente, Ricardo
A1  - Alsheimer, Manfred
T1  - A truncated lamin A in the Lmna\(^{−/−}\) mouse line: Implications for the understanding of laminopathies
JF  - Nucleus
N2  - During recent years a number of severe clinical syndromes, collectively termed laminopathies, turned out to be caused by various, distinct mutations in the human LMNA gene. Arising from this, remarkable progress has been made to unravel the molecular pathophysiology underlying these disorders. A great benefit in this context was the generation of an A-type lamin deficient mouse line (Lmna\(^{−/−}\)) by Sullivan and others,1 which has become one of the most frequently used models in the field and provided profound insights to many different aspects of A-type lamin function. Here, we report the unexpected finding that these mice express a truncated Lmna gene product on both transcriptional and protein level. Combining different approaches including mass spectrometry, we precisely define this product as a C-terminally truncated lamin A mutant that lacks domains important for protein interactions and post-translational processing. Based on our findings we discuss implications for the interpretation of previous studies using Lmna\(^{−/−}\) mice and the concept of human laminopathies.
KW  - nuclear organization
KW  - A-type lamins
KW  - LMNA mutations
KW  - laminopathies
KW  - nuclear envelope
KW  - nuclear lamina
Y1  - 2012
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-127281
VL  - 3
IS  - 5
ER  - 
TY  - JOUR
A1  - Weiße, Sebastian
A1  - Heddergott, Niko
A1  - Heydt, Matthias
A1  - Pflästerer, Daniel
A1  - Maier, Timo
A1  - Haraszti, Tamas
A1  - Grunze, Michael
A1  - Engstler, Markus
A1  - Rosenhahn, Axel
T1  - A Quantitative 3D Motility Analysis of Trypanosoma brucei by Use of Digital In-line Holographic Microscopy
JF  - PLoS One
N2  - We present a quantitative 3D analysis of the motility of the blood parasite Trypanosoma brucei. Digital in-line holographic microscopy has been used to track single cells with high temporal and spatial accuracy to obtain quantitative data on their behavior. Comparing bloodstream form and insect form trypanosomes as well as mutant and wildtype cells under varying external conditions we were able to derive a general two-state-run-and-tumble-model for trypanosome motility. Differences in the motility of distinct strains indicate that adaption of the trypanosomes to their natural environments involves a change in their mode of swimming.
KW  - african trypanosomes
KW  - actin cortex
KW  - flagellum
KW  - tracking
KW  - surface
KW  - models
Y1  - 2012
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-130666
VL  - 7
IS  - 5
ER  - 
TY  - JOUR
A1  - Staiger, Christine
A1  - Cadot, Sidney
A1  - Kooter, Raul
A1  - Dittrich, Marcus
A1  - Müller, Tobias
A1  - Klau, Gunnar W.
A1  - Wessels, Lodewyk F. A.
T1  - A Critical Evaluation of Network and Pathway-Based Classifiers for Outcome Prediction in Breast Cancer
JF  - PLoS One
N2  - Recently, several classifiers that combine primary tumor data, like gene expression data, and secondary data sources, such as protein-protein interaction networks, have been proposed for predicting outcome in breast cancer. In these approaches, new composite features are typically constructed by aggregating the expression levels of several genes. The secondary data sources are employed to guide this aggregation. Although many studies claim that these approaches improve classification performance over single genes classifiers, the gain in performance is difficult to assess. This stems mainly from the fact that different breast cancer data sets and validation procedures are employed to assess the performance. Here we address these issues by employing a large cohort of six breast cancer data sets as benchmark set and by performing an unbiased evaluation of the classification accuracies of the different approaches. Contrary to previous claims, we find that composite feature classifiers do not outperform simple single genes classifiers. We investigate the effect of (1) the number of selected features; (2) the specific gene set from which features are selected; (3) the size of the training set and (4) the heterogeneity of the data set on the performance of composite feature and single genes classifiers. Strikingly, we find that randomization of secondary data sources, which destroys all biological information in these sources, does not result in a deterioration in performance of composite feature classifiers. Finally, we show that when a proper correction for gene set size is performed, the stability of single genes sets is similar to the stability of composite feature sets. Based on these results there is currently no reason to prefer prognostic classifiers based on composite features over single genes classifiers for predicting outcome in breast cancer.
KW  - modules
KW  - protein-interaction networks
KW  - expression signature
KW  - classification
KW  - set
KW  - metastasis
KW  - stability
KW  - survival
KW  - database
KW  - markers
Y1  - 2012
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-131323
VL  - 7
IS  - 4
ER  -