Gunnar Dittmar

Bio: Gunnar Dittmar is an academic researcher from University of Luxembourg. The author has contributed to research in topics: Ubiquitin & Medicine. The author has an hindex of 35, co-authored 127 publications receiving 11002 citations. Previous affiliations of Gunnar Dittmar include Charité & Cardiff University.

Global quantification of mammalian gene expression control

Abstract: Gene expression is a multistep process that involves the transcription, translation and turnover of messenger RNAs and proteins. Although it is one of the most fundamental processes of life, the entire cascade has never been quantified on a genome-wide scale. Here we simultaneously measured absolute mRNA and protein abundance and turnover by parallel metabolic pulse labelling for more than 5,000 genes in mammalian cells. Whereas mRNA and protein levels correlated better than previously thought, corresponding half-lives showed no correlation. Using a quantitative model we have obtained the first genome-scale prediction of synthesis rates of mRNAs and proteins. We find that the cellular abundance of proteins is predominantly controlled at the level of translation. Genes with similar combinations of mRNA and protein stability shared functional properties, indicating that half-lives evolved under energetic and dynamic constraints. Quantitative information about all stages of gene expression provides a rich resource and helps to provide a greater understanding of the underlying design principles.

Senescence-associated reprogramming promotes cancer stemness

Abstract: Cellular senescence is a stress-responsive cell-cycle arrest program that terminates the further expansion of (pre-)malignant cells. Key signalling components of the senescence machinery, such as p16INK4a, p21CIP1 and p53, as well as trimethylation of lysine 9 at histone H3 (H3K9me3), also operate as critical regulators of stem-cell functions (which are collectively termed 'stemness'). In cancer cells, a gain of stemness may have profound implications for tumour aggressiveness and clinical outcome. Here we investigated whether chemotherapy-induced senescence could change stem-cell-related properties of malignant cells. Gene expression and functional analyses comparing senescent and non-senescent B-cell lymphomas from Eμ-Myc transgenic mice revealed substantial upregulation of an adult tissue stem-cell signature, activated Wnt signalling, and distinct stem-cell markers in senescence. Using genetically switchable models of senescence targeting H3K9me3 or p53 to mimic spontaneous escape from the arrested condition, we found that cells released from senescence re-entered the cell cycle with strongly enhanced and Wnt-dependent clonogenic growth potential compared to virtually identical populations that had been equally exposed to chemotherapy but had never been senescent. In vivo, these previously senescent cells presented with a much higher tumour initiation potential. Notably, the temporary enforcement of senescence in p53-regulatable models of acute lymphoblastic leukaemia and acute myeloid leukaemia was found to reprogram non-stem bulk leukaemia cells into self-renewing, leukaemia-initiating stem cells. Our data, which are further supported by consistent results in human cancer cell lines and primary samples of human haematological malignancies, reveal that senescence-associated stemness is an unexpected, cell-autonomous feature that exerts its detrimental, highly aggressive growth potential upon escape from cell-cycle blockade, and is enriched in relapse tumours. These findings have profound implications for cancer therapy, and provide new mechanistic insights into the plasticity of cancer cells.

Proteasome subunit Rpn1 binds ubiquitin-like protein domains.

Abstract: The yeast protein Rad23 belongs to a diverse family of proteins that contain an amino-terminal ubiquitin-like (UBL) domain. This domain mediates the binding of Rad23 to proteasomes, which in turn promotes DNA repair and modulates protein degradation, possibly by delivering ubiquitinylated cargo to proteasomes. Here we show that Rad23 binds proteasomes by directly interacting with the base subcomplex of the regulatory particle of the proteasome. A component of the base, Rpn1, specifically recognizes the UBL domain of Rad23 through its leucine-rich-repeat-like (LRR-like) domain. A second UBL protein, Dsk2, competes with Rad23 for proteasome binding, which suggests that the LRR-like domain of Rpn1 may participate in the recognition of several ligands of the proteasome. We propose that the LRR domain of Rpn1 may be positioned in the base to allow the cargo proteins carried by Rad23 to be presented to the proteasomal ATPases for unfolding. We also report that, contrary to expectation, the base subunit Rpn10 does not mediate the binding of UBL proteins to the proteasome in yeast, although it can apparently contribute to the binding of ubiquitin chains by intact proteasomes.

Global quantification of mammalian gene expression control

Abstract: Gene expression is a multistep process that involves the transcription, translation and turnover of messenger RNAs and proteins. Although it is one of the most fundamental processes of life, the entire cascade has never been quantified on a genome-wide scale. Here we simultaneously measured absolute mRNA and protein abundance and turnover by parallel metabolic pulse labelling for more than 5,000 genes in mammalian cells. Whereas mRNA and protein levels correlated better than previously thought, corresponding half-lives showed no correlation. Using a quantitative model we have obtained the first genome-scale prediction of synthesis rates of mRNAs and proteins. We find that the cellular abundance of proteins is predominantly controlled at the level of translation. Genes with similar combinations of mRNA and protein stability shared functional properties, indicating that half-lives evolved under energetic and dynamic constraints. Quantitative information about all stages of gene expression provides a rich resource and helps to provide a greater understanding of the underlying design principles.

The Perseus computational platform for comprehensive analysis of (prote)omics data.

Abstract: A main bottleneck in proteomics is the downstream biological analysis of highly multivariate quantitative protein abundance data generated using mass-spectrometry-based analysis. We developed the Perseus software platform (http://www.perseus-framework.org) to support biological and biomedical researchers in interpreting protein quantification, interaction and post-translational modification data. Perseus contains a comprehensive portfolio of statistical tools for high-dimensional omics data analysis covering normalization, pattern recognition, time-series analysis, cross-omics comparisons and multiple-hypothesis testing. A machine learning module supports the classification and validation of patient groups for diagnosis and prognosis, and it also detects predictive protein signatures. Central to Perseus is a user-friendly, interactive workflow environment that provides complete documentation of computational methods used in a publication. All activities in Perseus are realized as plugins, and users can extend the software by programming their own, which can be shared through a plugin store. We anticipate that Perseus's arsenal of algorithms and its intuitive usability will empower interdisciplinary analysis of complex large data sets.

The Ubiquitin-Proteasome Proteolytic Pathway: Destruction for the Sake of Construction

Abstract: Between the 1960s and 1980s, most life scientists focused their attention on studies of nucleic acids and the translation of the coded information. Protein degradation was a neglected area, conside...