The Proteomics of Cellular Signaling group uses proteomic analysis to assess the effect of post-translational modification in signaling pathways in both health and disease.
Proteins are the central players in cellular functions. They are functional units that are essential for cell structure. They are molecular machines, which can create power, regulate cellular signals or catalyse biochemical processes. Studying proteins can provide insight into what defines health and disease. We are using quantitative mass spectrometry-based proteomics as the central methodology of our research.
We are interested in two central questions: First, how does post-translational modification alter the interaction network and the signaling of cellular systems and tissues, and second how can we use proteomic analysis to analyse patient samples to develop diagnostic markers.
Regulation of immunological processes by ubiquitin signaling.
How are post-translational modifications (PTM) change cellular signaling using large-scale interactome studies
Development of biomarkers using targeted proteomics on patient cohorts.
How is the PTM code regulating the interactions of transcription factors?
Transcription factors (TF) are at the heart of cellular regulation. They bind to DNA and allow the transcription of genes. The regulation of TFs is essential for the normal function of a cell. TFs are highly modified by different PTMs. These PTMs can alter the binding of TFs to DNA directly, or they can change the interaction with other proteins, the so-called interactome. By studying all interactions simultaneously, we can get a general overview of how interactions are changing in response to PTM-modifications. This can lead to a better understanding of how misregulation of PTMs can lead to diseases. An example is the methylation of a single arginine residue in the transcription factor C/EBP ß, which leads to changes in fat cell differentiation.
Ramberger, E. et al. PRISMA and BioID disclose a motifs-based interactome of the intrinsically disordered transcription factor C/EBPα. iScience24, 102686 (2021).
Ramberger, E. et al. Universal peptide matrix pulldown approach for mapping mutation-, PTM-, and SLiM-dependent protein interactions. Mol Cell Proteomics.
Ramberger, E. et al. A comprehensive motifs-based interactome of the C/EBPα transcription factor. iScience (2020) doi:10.1101/2020.12.28.424569.
Dittmar, G. et al. PRISMA: Protein Interaction Screen on Peptide Matrix Reveals Interaction Footprints and Modifications- Dependent Interactome of Intrinsically Disordered C/EBPβ. iScience13, 351–370 (2019).
Development of diagnostic disease markers
Early diagnosis of diseases increases the chances for successful treatment. We are using targeted mass spectrometric methods to measure the composition of different body fluids. Here, identifying a set of proteins, which can be used to predict disease progression, is the project’s major goal.
Coll-de la Rubia, E. et al. Prognostic Biomarkers in Endometrial Cancer: A Systematic Review and Meta-Analysis. JCM 9, 1900 (2020).
Lesur, A. & Dittmar, G. The clinical potential of prm-PASEF mass spectrometry. Expert Review of Proteomics 18, 75–82 (2021).
Lesur, A. et al. Highly Multiplexed Targeted Proteomics Acquisition on a TIMS-QTOF. Anal. Chem. 93, 1383–1392 (2021).
Regulation of the transcription factor HIF1-alpha by the ubiquitin-system
The transcription factor HIF1a is the central regulator for sensing oxygen levels in a cell and regulating the cell’s metabolism in response to that. Recent data from different laboratories points to alternative regulatory pathways involved in regulating Hif1a besides the well-described regulation by the ubiquitin-E3 ligase VHL. We are using a combination of molecular biology-based techniques and proteomic analysis to shed light on these new regulatory pathways.
Necessary cookies are absolutely essential for the website to function properly. These cookies ensure basic functionalities and security features of the website, anonymously.
5 months 27 days
This cookie is set by the Google recaptcha service to identify bots to protect the website against malicious spam attacks.
Set by the GDPR Cookie Consent plugin, this cookie is used to record the user consent for the cookies in the "Advertisement" category .
Set by the GDPR Cookie Consent plugin, this cookie is used to record the user consent for the cookies in the "Analytics" category .
The cookie is set by the GDPR Cookie Consent plugin to record the user consent for the cookies in the category "Functional".
Set by the GDPR Cookie Consent plugin, this cookie is used to record the user consent for the cookies in the "Necessary" category .
Set by the GDPR Cookie Consent plugin, this cookie is used to store the user consent for cookies in the category "Others".
Set by the GDPR Cookie Consent plugin, this cookie is used to store the user consent for cookies in the category "Performance".
Records the default button state of the corresponding category & the status of CCPA. It works only in coordination with the primary cookie.
The JSESSIONID cookie is used by New Relic to store a session identifier so that New Relic can monitor session counts for an application.
This cookie is native to PHP applications. The cookie is used to store and identify a users' unique session ID for the purpose of managing user session on the website. The cookie is a session cookies and is deleted when all the browser windows are closed.
Analytical cookies are used to understand how visitors interact with the website. These cookies provide information on metrics such as number of visitors, bounce rate, traffic source, etc.
The _ga cookie, installed by Google Analytics, calculates visitor, session and campaign data and also keeps track of site usage for the site's analytics report. The cookie stores information anonymously and assigns a randomly generated number to recognize unique visitors.
This cookie is installed by Google Analytics.
Set by Google to distinguish users.
Installed by Google Analytics, _gid cookie stores information on how visitors use a website, while also creating an analytics report of the website's performance. Some of the data that are collected include the number of visitors, their source, and the pages they visit anonymously.
Linkedin set this cookie to store information about the time a sync took place with the lms_analytics cookie.
YouTube sets this cookie via embedded youtube-videos and registers anonymous statistical data.