Marcus Krantz
Position: Researcher School/office: School of Medical SciencesEmail: bWFyY3VzLmtyYW50ejtvcnUuc2U=
Phone: +46 19 302490
Room: X2214
About Marcus Krantz
Marcus Krantz is a researcher in Systems Biology at the School of Medical Sciences and the Inflammatory Response and Infection Susceptibility Centre (iRiSC) since 2022. He was previously a junior group leader at the Humboldt-Universität zu Berlin, where he developed rxncon, the reaction-contingency language for building and modelling large-scale signal transduction networks. His research focusses on understanding how cells process information and how they use the information to reach decisions, for example to divide or to halt the cell division cycle depending on internal and external signals.
Research
Cells monitor their internal state and perceive their surrounding through signal transduction pathways, which integrate these different cues to control cell behaviour. Hence, cellular signal transduction is critical for almost all aspects of life, from developmental processes to the constant maintenance of body homeostasis. At iRiSC, we are particularly interested in understanding how signal transduction controls the immune response and inflammatory processes, and to understand how differences in those functions differ between healthy and pathological inflammation.
Inflammation is an essential protective mechanism that occurs in response to pathogen exposure or tissue damage, resulting in increased recruitment and activation of immune cells in the damaged or infected tissue that is necessary for recovery and healing. However, many non-infectious diseases are associated with pathological inflammation, as in allergy, autoimmune diseases and as a side effect of e.g. diabetes or cancer. Normally, inflammation is initiated by the detection of pathogens or tissue damage, but erroneous signal transduction can lead to spontaneous or hyper-activation of the inflammatory response, for example through genetic polymorphisms that increase the risk of spontaneous inflammation.
We want to understand how signal transduction shapes inflammation in response to different triggers, and how this response differs between individuals. To this end, we use a systems biology approach: We assemble knowledge on the individual components of these signalling processes into a network, akin to a road map for inflammation control. The focus of my work is on building and analysing these network models. The goal is to be able to explain how cells react to different triggers, why different persons react differently, and to predict the effect of a specific treatment in a specific person.
Teaching
Marcus Krantz gives lectures in systems biology and trains students to use systems biology approaches to go from knowledge on details to a holistic understanding of a system. He acts as a PBL teacher and as coordinator for the 5th semester of the medical program at the School of Medical Sciences. He has also been a teacher at several high-profile international training courses in systems biology.
Research groups
Publications
Articles in journals
- Krantz, M. , Eklund, D. , Särndahl, E. & Hedbrant, A. (2023). A detailed molecular network map and model of the NLRP3 inflammasome. Frontiers in Immunology, 14. [BibTeX]
- Carretero Chavez, W. , Krantz, M. , Klipp, E. & Kufareva, I. (2023). kboolnet: a toolkit for the verification, validation, and visualization of reaction-contingency (rxncon) models. BMC Bioinformatics, 24 (1). [BibTeX]
- Adler, S. O. , Spiesser, T. W. , Uschner, F. , Münzner, U. , Hahn, J. , Krantz, M. & Klipp, E. (2022). A yeast cell cycle model integrating stress, signaling, and physiology. FEMS yeast research (Print), 22 (1). [BibTeX]
- Münzner, U. , Mori, T. , Krantz, M. , Klipp, E. & Akutsu, T. (2022). Identification of periodic attractors in Boolean networks using a priori information. PloS Computational Biology, 18 (1). [BibTeX]
- Romers, J. , Thieme, S. , Münzner, U. & Krantz, M. (2020). A scalable method for parameter-free simulation and validation of mechanistic cellular signal transduction network models. npj Systems Biology and Applications, 6 (1). [BibTeX]
- Münzner, U. , Klipp, E. & Krantz, M. (2019). A comprehensive, mechanistically detailed, and executable model of the cell division cycle in Saccharomyces cerevisiae. Nature Communications, 10 (1). [BibTeX]
- Romers, J. , Thieme, S. , Münzner, U. & Krantz, M. (2019). Using rxncon to Develop Rule-Based Models. Methods in Molecular Biology, 71-118. [BibTeX]
- Cvijovic, M. , Höfer, T. , Aćimović, J. , Alberghina, L. , Almaas, E. , Besozzi, D. , Blomberg, A. , Bretschneider, T. & et al. (2016). Strategies for structuring interdisciplinary education in Systems Biology: an European perspective. npj Systems Biology and Applications, 2 (1). [BibTeX]
- Spiesser, T. , Kühn, C. , Krantz, M. & Klipp, E. (2016). The MYpop toolbox: Putting yeast stress responses in cellular context on single cell and population scales. Biotechnology Journal, 11 (9), 1158-1168. [BibTeX]
- Waltemath, D. , Krantz, M. & Schrieber, F. (2016). Toward community standards and software for Whole-Cell Modeling. IEEE Transactions on Biomedical Engineering, 63 (10), 2007-2014. [BibTeX]
- Spiesser, T. W. , Kühn, C. , Krantz, M. & Klipp, E. (2015). Bud-Localization of CLB2 mRNA can constitute a growth rate dependent daughter sizer. PloS Computational Biology, 11 (4). [BibTeX]
- Lubitz, T. , Welkenhuysen, N. , Shashkova, S. , Bendrioua, L. , Hohmann, S. , Klipp, E. & Krantz, M. (2015). Network reconstruction and validation of the Snf1/AMPK pathway in baker’s yeast based on a comprehensive literature review. npj Systems Biology and Applications, 1. [BibTeX]
- Mori, T. , Flöttmann, M. , Krantz, M. , Akutsu, T. & Klipp, E. (2015). Stochastic simulation of Boolean rxncon models: towards quantitative analysis of large signaling networks. BMC Systems Biology, 9. [BibTeX]
- García‐Salcedo, R. , Lubitz, T. , Beltran, G. , Elbing, K. , Tian, Y. , Frey, S. , Wolkenhauer, O. , Krantz, M. & et al. (2014). Glucose de‐repression by yeast AMP‐activated protein kinase SNF1 is controlled via at least two independent steps. The FEBS Journal, 281 (7), 1901-1917. [BibTeX]
- Krause, F. , Schulz, M. , Ripkens, B. , Flöttmann, M. , Krantz, M. , Klipp, E. & Handorf, T. (2013). Biographer: web-based editing and rendering of SBGN compliant biochemical networks. Bioinformatics, 29 (11), 1467-1468. [BibTeX]
- Geijer, C. , Medrala‐Klein, D. , Petelenz‐Kurdziel, E. , Ericsson, A. , Smedh, M. , Andersson, M. , Goksör, M. , Nadal‐Ribelles, M. & et al. (2013). Initiation of the transcriptional response to hyperosmotic shock correlates with the potential for volume recovery. The FEBS Journal, 280 (16), 3854-3867. [BibTeX]
- Flöttmann, M. , Krause, F. , Klipp, E. & Krantz, M. (2013). Reaction-contingency based bipartite Boolean modelling. BMC Systems Biology, 7. [BibTeX]
- Tiger, C. , Krause, F. , Cedersund, G. , Palmér, R. , Klipp, E. , Hohmann, S. , Kitano, H. & Krantz, M. (2012). A framework for mapping, visualisation and automatic model creation of signal‐transduction networks. Molecular Systems Biology, 8. [BibTeX]
- Spiesser, T. W. , Müller, C. , Schreiber, G. , Krantz, M. & Klipp, E. (2012). Size homeostasis can be intrinsic to growing cell populations and explained without size sensing or signalling. The FEBS Journal, 279 (22), 4213-4230. [BibTeX]
- Geijer, C. , Pirkov, I. , Vongsangnak, W. , Ericsson, A. , Nielsen, J. , Krantz, M. & Hohmann, S. (2012). Time course gene expression profiling of yeast spore germination reveals a network of transcription factors orchestrating the global response. BMC Genomics, 13. [BibTeX]
- Babazadeh, R. , Moghadas Jafari, S. , Zackrisson, M. , Blomberg, A. , Hohmann, S. , Warringer, J. & Krantz, M. (2011). TheAshbya gossypiiEF-1αpromoter of the ubiquitously used MX cassettes is toxic to Saccharomyces cerevisiae. FEBS Letters, 585 (24), 3907-3913. [BibTeX]
- Krantz, M. , Ahmadpour, D. , Ottosson, L. , Warringer, J. , Waltermann, C. , Nordlander, B. , Klipp, E. , Blomberg, A. & et al. (2009). Robustness and fragility in the yeast high osmolarity glycerol (HOG) signal‐transduction pathway. Molecular Systems Biology, 5. [BibTeX]
- Hohmann, S. , Krantz, M. & Nordlander, B. (2007). Yeast Osmoregulation. Methods in Enzymology, 428, 29-45. [BibTeX]
- Krantz, M. , Becit, E. & Hohmann, S. (2006). Comparative analysis of HOG pathway proteins to generate hypotheses for functional analysis. Current Genetics, 49 (3), 152-165. [BibTeX]
- Krantz, M. , Becit, E. & Hohmann, S. (2006). Comparative genomics of the HOG-signalling system in fungi. Current Genetics, 49 (3), 137-151. [BibTeX]
- Krantz, M. , Nordlander, B. , Valadi, H. , Johansson, M. , Gustafsson, L. & Hohmann, S. (2004). Anaerobicity prepares saccharomyces cerevisiae cells for faster adaptation to osmotic shock. Eukaryotic Cell, 3 (6), 1381-1390. [BibTeX]
- Rep, M. , Krantz, M. , Thevelein, J. M. & Hohmann, S. (2000). The transcriptional response of saccharomyces cerevisiae to osmotic shock. Journal of Biological Chemistry, 275 (12), 8290-8300. [BibTeX]
Articles, reviews/surveys
- Cvijovic, M. , Almquist, J. , Hagmar, J. , Hohmann, S. , Kaltenbach, H. , Klipp, E. , Krantz, M. , Mendes, P. & et al. (2014). Bridging the gaps in systems biology. Molecular Genetics and Genomics, 289 (5), 727-734. [BibTeX]
- Rother, M. , Münzner, U. , Thieme, S. & Krantz, M. (2013). Information content and scalability in signal transduction network reconstruction formats. Molecular Biosystems, 9 (8), 1993-2004. [BibTeX]
Chapters in books
- Münzner, U. , Lubitz, T. , Klipp, E. & Krantz, M. (2017). Toward Genome‐Scale Models of Signal Transduction Networks. In: Jens Nielsen; Stefan Hohmann, Systems Biology (pp. 215-242). . Wiley-VCH Verlagsgesellschaft. [BibTeX]
- Nordlander, B. , Krantz, M. & Hohmann, S. (2008). Hog1-mediated Metabolic Adjustments Following Hyperosmotic Shock in the Yeast Saccharomyces cerevisiae. In: Francesc Posas; Angel R. Nebreda, Stress-Activated Protein Kinases (pp. 141-158). Berlin: Springer-Verlag Berlin Heidelberg. [BibTeX]
- Krantz, M. & Hohmann, S. (2005). Employing protein size in the functional analysis of orthologous proteins, as illustrated with the yeast HOG pathway. In: Per Sunnerhagen; Jure Piškur, Comparative Genomics: Using Fungi as Models (pp. 131-143). . Springer. [BibTeX]