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Dive into the research topics where Matthias Selbach is active.

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Featured researches published by Matthias Selbach.


Nature | 2011

Global quantification of mammalian gene expression control

Björn Schwanhäusser; Dorothea Busse; Na Li; Gunnar Dittmar; Johannes Schuchhardt; Jana Wolf; Wei Chen; Matthias Selbach

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.


Nature | 2008

Widespread changes in protein synthesis induced by microRNAs

Matthias Selbach; Björn Schwanhäusser; Nadine Thierfelder; Zhuo Fang; Raya Khanin; Nikolaus Rajewsky

Animal microRNAs (miRNAs) regulate gene expression by inhibiting translation and/or by inducing degradation of target messenger RNAs. It is unknown how much translational control is exerted by miRNAs on a genome-wide scale. We used a new proteomic approach to measure changes in synthesis of several thousand proteins in response to miRNA transfection or endogenous miRNA knockdown. In parallel, we quantified mRNA levels using microarrays. Here we show that a single miRNA can repress the production of hundreds of proteins, but that this repression is typically relatively mild. A number of known features of the miRNA-binding site such as the seed sequence also govern repression of human protein synthesis, and we report additional target sequence characteristics. We demonstrate that, in addition to downregulating mRNA levels, miRNAs also directly repress translation of hundreds of genes. Finally, our data suggest that a miRNA can, by direct or indirect effects, tune protein synthesis from thousands of genes.


Nature Protocols | 2009

A practical guide to the MaxQuant computational platform for SILAC-based quantitative proteomics

Jürgen Cox; Ivan Matic; Maximiliane Hilger; Nagarjuna Nagaraj; Matthias Selbach; J. Olsen; Matthias Mann

MaxQuant is a quantitative proteomics software package designed for analyzing large mass spectrometric data sets. It is specifically aimed at high-resolution mass spectrometry (MS) data. Currently, Thermo LTQ-Orbitrap and LTQ-FT-ICR instruments are supported and Mascot is used as a search engine. This protocol explains step by step how to use MaxQuant on stable isotope labeling by amino acids in cell culture (SILAC) data obtained with double or triple labeling. Complex experimental designs, such as time series and drug-response data, are supported. A standard desktop computer is sufficient to fulfill the computational requirements. The workflow has been stress tested with more than 1,000 liquid chromatography/mass spectrometry runs in a single project. In a typical SILAC proteome experiment, hundreds of thousands of peptides and thousands of proteins are automatically and reliably quantified. Additional information for identified proteins, such as Gene Ontology, domain composition and pathway membership, is provided in the output tables ready for further bioinformatics analysis. The software is freely available at the MaxQuant home page.


Immunity | 2010

Quantitative Proteomics Reveals Subset-Specific Viral Recognition in Dendritic Cells

Christian A. Luber; Jürgen Cox; Henning Lauterbach; Ben Fancke; Matthias Selbach; Jürg Tschopp; Shizuo Akira; Marian Wiegand; Hubertus Hochrein; Meredith O'Keeffe; Matthias Mann

Dendritic cell (DC) populations consist of multiple subsets that are essential orchestrators of the immune system. Technological limitations have so far prevented systems-wide accurate proteome comparison of rare cell populations in vivo. Here, we used high-resolution mass spectrometry-based proteomics, combined with label-free quantitation algorithms, to determine the proteome of mouse splenic conventional and plasmacytoid DC subsets to a depth of 5,780 and 6,664 proteins, respectively. We found mutually exclusive expression of pattern recognition pathways not previously known to be different among conventional DC subsets. Our experiments assigned key viral recognition functions to be exclusively expressed in CD4(+) and double-negative DCs. The CD8alpha(+) DCs largely lack the receptors required to sense certain viruses in the cytoplasm. By avoiding activation via cytoplasmic receptors, including retinoic acid-inducible gene I, CD8alpha(+) DCs likely gain a window of opportunity to process and present viral antigens before activation-induced shutdown of antigen presentation pathways occurs.


Proteomics | 2009

Global analysis of cellular protein translation by pulsed SILAC

Björn Schwanhäusser; Manfred Gossen; Gunnar Dittmar; Matthias Selbach

Current methods for system‐wide gene expression analysis detect changes in mRNA abundance, but neglect regulation at the level of translation. Pulse labeling with stable isotopes has been used to measure protein turnover rates, but this does not directly provide information about translation rates. Here, we developed pulsed stable isotope labeling by amino acids in cell culture (pSILAC) with two heavy isotope labels to directly quantify protein translation on a proteome‐wide scale. We applied the method to cellular iron homeostasis as a model system and demonstrate that it can confidently identify proteins that are translationally regulated by iron availability.


Cell | 2013

Orchestrated intron retention regulates normal granulocyte differentiation.

Justin Wong; William Ritchie; Olivia A. Ebner; Matthias Selbach; Jason Wong; Yizhou Huang; Dadi Gao; Natalia Pinello; Maria Gonzalez; Kinsha Baidya; Annora Thoeng; Teh-Liane Khoo; Charles G. Bailey; Jeff Holst; John E.J. Rasko

Intron retention (IR) is widely recognized as a consequence of mis-splicing that leads to failed excision of intronic sequences from pre-messenger RNAs. Our bioinformatic analyses of transcriptomic and proteomic data of normal white blood cell differentiation reveal IR as a physiological mechanism of gene expression control. IR regulates the expression of 86 functionally related genes, including those that determine the nuclear shape that is unique to granulocytes. Retention of introns in specific genes is associated with downregulation of splicing factors and higher GC content. IR, conserved between human and mouse, led to reduced mRNA and protein levels by triggering the nonsense-mediated decay (NMD) pathway. In contrast to the prevalent view that NMD is limited to mRNAs encoding aberrant proteins, our data establish that IR coupled with NMD is a conserved mechanism in normal granulopoiesis. Physiological IR may provide an energetically favorable level of dynamic gene expression control prior to sustained gene translation.


Molecular & Cellular Proteomics | 2010

The SILAC Fly Allows for Accurate Protein Quantification in Vivo

Sury; Jia-Xuan Chen; Matthias Selbach

Stable isotope labeling by amino acids in cell culture (SILAC) is widely used to quantify protein abundance in tissue culture cells. Until now, the only multicellular organism completely labeled at the amino acid level was the laboratory mouse. The fruit fly Drosophila melanogaster is one of the most widely used small animal models in biology. Here, we show that feeding flies with SILAC-labeled yeast leads to almost complete labeling in the first filial generation. We used these “SILAC flies” to investigate sexual dimorphism of protein abundance in D. melanogaster. Quantitative proteome comparison of adult male and female flies revealed distinct biological processes specific for each sex. Using a tudor mutant that is defective for germ cell generation allowed us to differentiate between sex-specific protein expression in the germ line and somatic tissue. We identified many proteins with known sex-specific expression bias. In addition, several new proteins with a potential role in sexual dimorphism were identified. Collectively, our data show that the SILAC fly can be used to accurately quantify protein abundance in vivo. The approach is simple, fast, and cost-effective, making SILAC flies an attractive model system for the emerging field of in vivo quantitative proteomics.


Nature Methods | 2016

Detecting actively translated open reading frames in ribosome profiling data

Lorenzo Calviello; Neelanjan Mukherjee; Emanuel Wyler; Henrik Zauber; Antje Hirsekorn; Matthias Selbach; Markus Landthaler; Benedikt Obermayer; Uwe Ohler

RNA-sequencing protocols can quantify gene expression regulation from transcription to protein synthesis. Ribosome profiling (Ribo-seq) maps the positions of translating ribosomes over the entire transcriptome. We have developed RiboTaper (available at https://ohlerlab.mdc-berlin.de/software/), a rigorous statistical approach that identifies translated regions on the basis of the characteristic three-nucleotide periodicity of Ribo-seq data. We used RiboTaper with deep Ribo-seq data from HEK293 cells to derive an extensive map of translation that covered open reading frame (ORF) annotations for more than 11,000 protein-coding genes. We also found distinct ribosomal signatures for several hundred upstream ORFs and ORFs in annotated noncoding genes (ncORFs). Mass spectrometry data confirmed that RiboTaper achieved excellent coverage of the cellular proteome. Although dozens of novel peptide products were validated in this manner, few of the currently annotated long noncoding RNAs appeared to encode stable polypeptides. RiboTaper is a powerful method for comprehensive de novo identification of actively used ORFs from Ribo-seq data.


Proceedings of the National Academy of Sciences of the United States of America | 2009

The tyrosine phosphatase Shp2 (PTPN11) directs Neuregulin-1/ErbB signaling throughout Schwann cell development

Katja S. Grossmann; Hagen Wende; Florian E. Paul; Cyril Cheret; Alistair N. Garratt; Sandra Zurborg; Konstantin Feinberg; Daniel Besser; Herbert Schulz; Elior Peles; Matthias Selbach; Walter Birchmeier; Carmen Birchmeier

The nonreceptor tyrosine phosphatase Shp2 (PTPN11) has been implicated in tyrosine kinase, cytokine, and integrin receptor signaling. We show here that conditional mutation of Shp2 in neural crest cells and in myelinating Schwann cells resulted in deficits in glial development that are remarkably similar to those observed in mice mutant for Neuregulin-1 (Nrg1) or the Nrg1 receptors, ErbB2 and ErbB3. In cultured Shp2 mutant Schwann cells, Nrg1-evoked cellular responses like proliferation and migration were virtually abolished, and Nrg1-dependent intracellular signaling was altered. Pharmacological inhibition of Src family kinases mimicked all cellular and biochemical effects of the Shp2 mutation, implicating Src as a primary Shp2 target during Nrg1 signaling. Together, our genetic and biochemical analyses demonstrate that Shp2 is an essential component in the transduction of Nrg1/ErbB signals.


Nature | 2013

Corrigendum: Global quantification of mammalian gene expression control

Björn Schwanhäusser; Dorothea Busse; Na Li; Gunnar Dittmar; Johannes Schuchhardt; Jana Wolf; Wei Chen; Matthias Selbach

This corrects the article DOI: 10.1038/nature10098

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Marieluise Kirchner

Max Delbrück Center for Molecular Medicine

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Erik McShane

Max Delbrück Center for Molecular Medicine

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Markus Landthaler

Max Delbrück Center for Molecular Medicine

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Björn Schwanhäusser

Max Delbrück Center for Molecular Medicine

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Carmen Birchmeier

Max Delbrück Center for Molecular Medicine

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Nikolaus Rajewsky

Max Delbrück Center for Molecular Medicine

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Gunnar Dittmar

Max Delbrück Center for Molecular Medicine

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Koshi Imami

Max Delbrück Center for Molecular Medicine

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Uwe Ohler

Max Delbrück Center for Molecular Medicine

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