Prof. Dr. Marcus Krüger

Research Area: Quantitative Proteomics

Website: http://krueger.cecad-labs.de

1. Research Background:

The development of complex organisms during evolution requires synchronized interaction in order to coordinate the growth and function of cells and tissues that are spatially distant. For example, cells can communicate across distances through endocrine signals by secreting small molecules and proteins. Adult skeletal muscle is a highly dynamic and plastic tissue that produces and secretes trophic factors, including cytokines, growth factors and myokines. A tremendous number of proteins is released to the blood stream by skeletal muscle and adipose tissue. These factors have been shown to transmit signals to other tissues such as liver, brain and immune-related cells. It has been shown that metabolic syndromes (diabetes mellitus type II), inflammation and cancer influence this communication and contribute to the overall pathology. Conversely, physical exercise induces the secretion of molecules, which are capable of modulating systemic metabolism and these secreted molecules facilitate crosstalk between tissues and thus improve overall metabolic health. In humans, the body composition changes dramatically during the aging process and is characterized by a decrease in bone and muscle mass and an increase in fat tissue.

It is currently unclear to what extent inter-organ communication is involved in this process and which proteins are transmitting over large distance. Therefore, understanding which proteins mediate communication between organs is the key to understand age-related changes.

2. Research questions addresses by the group:

A major challenge in the identification of secreted proteins are the low concentrations in the blood and the differentiation of the protein origin in the target organ. With this proposal, we aim to identify secreted proteins from muscle and fat tissue. Furthermore, we will decipher which organs take up proteins secreted by muscle and adipocytes under different physiological conditions. The proposed project aims to identify these molecules by highly selective “click” chemistry. A prerequisite is tissue specific labeling of proteins for click chemistry. To this end, we have established a mouse line with tissue specific expression of a mutated Methionine t-RNA ligase (MetRS*). MetRS* catalytic cavity recognizes the methionine analog and click-chemistry reagent Azidonorleucine (ANL). Thus, cells expressing MetRS* metabolically label their proteome and make it accessible to click chemistry based experiments.

3. Possible projects:

  1. Studying the influence of protein secretion under high fat diet conditions and decipher the cross-talk between adipocytes and immune-related cells in visceral fat tissue in living animals.
  2. Protein turnover studies in the mouse using a tissue-specific MetRS* expression to identify newly synthesized proteins under stress-related conditions

4. Applied Methods and model organisms:

All studies focusing on the MetRS mouse model and high resolution mass spectrometry (Exploris and Eclipse). Proteomics sample preparation, click chemistry, TMT labeling and chromatographic separation techniques, including size exclusion and high pH reversed phase chromatography will be used in this project. Bioinformatics and statistical analysis using different software tools will be an important part of the project to analyse the complex datasets. Protein turnover rates will be achieved by the pulsed stable isotope labeling in vivo. Data acquisition will be performed in a data-dependent (DDA) and data-independent (DIA) approach. MaxQuant, Skyline and Spectronaut are established software tools and will be used for data analysis.

5. Desirable skills and qualifications:

Basic knowledge in cell and molecular biology, quantitative proteomics and interest in bioinformatics analysis of large-scale datasets.

6. References:

  1. Tellkamp, F., Lang, F., Ibáñez Ricoma, A., Abraham, L., Quezada, G., Günther, S., Looso, M., Tann, F.J., Müller, D., Cemic, F., Hemberger, J., Steinfartz, S. and Krüger, M. (2020). Proteomics of Galápagos marine iguanas links function of femoral gland proteins to the immune system. Mol Cell Proteomics. Accepted manuscript.
  2. Kallabis, S., Abraham, L., Müller, S., Dzialas, V., Türk, C., Wiederstein, J.L., Bock, T., Nolte, H., Nogara, L., Blaauw, B., Braun, T., and Krüger, M. (2020). High-throughput proteomics fiber typing (ProFiT) for comprehensive characterization of single skeletal muscle fibers. Skelet Muscle 10, 7.
  3. Wiederstein, J.L., Nolte, H., Günther, S., Piller, T., Baraldo, M., Kostin, S., Bloch, W., Schindler, N., Sandri, M., Blaauw, B., Braun, T., Hölper, S., Krüger, M. (2018). Skeletal Muscle-Specific Methyltransferase METTL21C Trimethylates p97 and Regulates Autophagy-Associated Protein Breakdown. Cell Reports 23(5), 1342-56.
  4. Lang, F., Aravamudhan, S., Nolte, H., Türk, C., Hölper, S., Müller, S., Günther, S., Blaauw, B., Braun, T., Krüger, M. (2017). Dynamic changes in the mouse skeletal muscle proteome during denervation-induced atrophy. Dis Model Mech. 10(7), 881-96.
  5. Islam, S., Nolte, H., Jacob, W., Ziegler, A.B., Pütz, S., Grosjean, Y., Szczepanowska, K., Trifunovic, A., Braun, T., Heumann, H., Heumann, R., Hovemann, B., Moore, D.J., Krüger, M. (2016). Human R1441C LRRK2 regulates the synaptic vesicle proteome and phosphoproteome in a Drosophila model of Parkinson's disease. Hum Mol Genet. 25(24), 5365-82.
  6. Hölper, S., Nolte, H., Bober, E., Braun, T., Krüger, M. (2015). Dissection of metabolic pathways in the Db/Db mouse model by integrative proteome and acetylome analysis Molecular BioSystems 3, 908-22.