Publications by authors named "Katharina Baum"

12 Publications

  • Page 1 of 1

Systematic Identification of MACC1-Driven Metabolic Networks in Colorectal Cancer.

Cancers (Basel) 2021 Feb 26;13(5). Epub 2021 Feb 26.

German Cancer Consortium, Deutsches Krebsforschungzentrum (DKFZ), 69120 Heidelberg, Germany.

MACC1 is a prognostic and predictive metastasis biomarker for more than 20 solid cancer entities. However, its role in cancer metabolism is not sufficiently explored. Here, we report on how MACC1 impacts the use of glucose, glutamine, lactate, pyruvate and fatty acids and show the comprehensive analysis of MACC1-driven metabolic networks. We analyzed concentration-dependent changes in nutrient use, nutrient depletion, metabolic tracing employing C-labeled substrates, and in vivo studies. We found that MACC1 permits numerous effects on cancer metabolism. Most of those effects increased nutrient uptake. Furthermore, MACC1 alters metabolic pathways by affecting metabolite production or turnover from metabolic substrates. MACC1 supports use of glucose, glutamine and pyruvate via their increased depletion or altered distribution within metabolic pathways. In summary, we demonstrate that MACC1 is an important regulator of metabolism in cancer cells.
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http://dx.doi.org/10.3390/cancers13050978DOI Listing
February 2021

Oscillations of Delta-like1 regulate the balance between differentiation and maintenance of muscle stem cells.

Nat Commun 2021 02 26;12(1):1318. Epub 2021 Feb 26.

Developmental Biology/Signal Transduction, Max-Delbrück-Center for Molecular Medicine, Berlin, Germany.

Cell-cell interactions mediated by Notch are critical for the maintenance of skeletal muscle stem cells. However, dynamics, cellular source and identity of functional Notch ligands during expansion of the stem cell pool in muscle growth and regeneration remain poorly characterized. Here we demonstrate that oscillating Delta-like 1 (Dll1) produced by myogenic cells is an indispensable Notch ligand for self-renewal of muscle stem cells in mice. Dll1 expression is controlled by the Notch target Hes1 and the muscle regulatory factor MyoD. Consistent with our mathematical model, our experimental analyses show that Hes1 acts as the oscillatory pacemaker, whereas MyoD regulates robust Dll1 expression. Interfering with Dll1 oscillations without changing its overall expression level impairs self-renewal, resulting in premature differentiation of muscle stem cells during muscle growth and regeneration. We conclude that the oscillatory Dll1 input into Notch signaling ensures the equilibrium between self-renewal and differentiation in myogenic cell communities.
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http://dx.doi.org/10.1038/s41467-021-21631-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7910593PMC
February 2021

Inhibiting phosphoglycerate dehydrogenase counteracts chemotherapeutic efficacy against MYCN-amplified neuroblastoma.

Int J Cancer 2021 Mar 17;148(5):1219-1232. Epub 2020 Dec 17.

Department of Pediatric Hematology and Oncology, Charité-Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany.

Here we sought metabolic alterations specifically associated with MYCN amplification as nodes to indirectly target the MYCN oncogene. Liquid chromatography-mass spectrometry-based proteomics identified seven proteins consistently correlated with MYCN in proteomes from 49 neuroblastoma biopsies and 13 cell lines. Among these was phosphoglycerate dehydrogenase (PHGDH), the rate-limiting enzyme in de novo serine synthesis. MYCN associated with two regions in the PHGDH promoter, supporting transcriptional PHGDH regulation by MYCN. Pulsed stable isotope-resolved metabolomics utilizing C-glucose labeling demonstrated higher de novo serine synthesis in MYCN-amplified cells compared to cells with diploid MYCN. An independence of MYCN-amplified cells from exogenous serine and glycine was demonstrated by serine and glycine starvation, which attenuated nucleotide pools and proliferation only in cells with diploid MYCN but did not diminish these endpoints in MYCN-amplified cells. Proliferation was attenuated in MYCN-amplified cells by CRISPR/Cas9-mediated PHGDH knockout or treatment with PHGDH small molecule inhibitors without affecting cell viability. PHGDH inhibitors administered as single-agent therapy to NOG mice harboring patient-derived MYCN-amplified neuroblastoma xenografts slowed tumor growth. However, combining a PHGDH inhibitor with the standard-of-care chemotherapy drug, cisplatin, revealed antagonism of chemotherapy efficacy in vivo. Emergence of chemotherapy resistance was confirmed in the genetic PHGDH knockout model in vitro. Altogether, PHGDH knockout or inhibition by small molecules consistently slows proliferation, but stops short of killing the cells, which then establish resistance to classical chemotherapy. Although PHGDH inhibition with small molecules has produced encouraging results in other preclinical cancer models, this approach has limited attractiveness for patients with neuroblastoma.
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http://dx.doi.org/10.1002/ijc.33423DOI Listing
March 2021

N-Myc-induced metabolic rewiring creates novel therapeutic vulnerabilities in neuroblastoma.

Sci Rep 2020 04 28;10(1):7157. Epub 2020 Apr 28.

Department of Medical Oncology, West German Cancer Center, University Hospital Essen, University of Duisburg-Essen, Essen, Germany.

N-Myc is a transcription factor that is aberrantly expressed in many tumor types and is often correlated with poor patient prognosis. Recently, several lines of evidence pointed to the fact that oncogenic activation of Myc family proteins is concomitant with reprogramming of tumor cells to cope with an enhanced need for metabolites during cell growth. These adaptions are driven by the ability of Myc proteins to act as transcriptional amplifiers in a tissue-of-origin specific manner. Here, we describe the effects of N-Myc overexpression on metabolic reprogramming in neuroblastoma cells. Ectopic expression of N-Myc induced a glycolytic switch that was concomitant with enhanced sensitivity towards 2-deoxyglucose, an inhibitor of glycolysis. Moreover, global metabolic profiling revealed extensive alterations in the cellular metabolome resulting from overexpression of N-Myc. Limited supply with either of the two main carbon sources, glucose or glutamine, resulted in distinct shifts in steady-state metabolite levels and significant changes in glutathione metabolism. Interestingly, interference with glutamine-glutamate conversion preferentially blocked proliferation of N-Myc overexpressing cells, when glutamine levels were reduced. Thus, our study uncovered N-Myc induction and nutrient levels as important metabolic master switches in neuroblastoma cells and identified critical nodes that restrict tumor cell proliferation.
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http://dx.doi.org/10.1038/s41598-020-64040-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7188804PMC
April 2020

Analysis of correlation-based biomolecular networks from different omics data by fitting stochastic block models.

F1000Res 2019 14;8:465. Epub 2019 Apr 14.

Bioinformatics and Modelling, Luxembourg Institute of Health, Strassen, Luxembourg.

Biological entities such as genes, promoters, mRNA, metabolites or proteins do not act alone, but in concert in their network context. Modules, i.e., groups of nodes with similar topological properties in these networks characterize important biological functions of the underlying biomolecular system. Edges in such molecular networks represent regulatory and physical interactions, and comparing them between conditions provides valuable information on differential molecular mechanisms. However, biological data is inherently noisy and network reduction techniques can propagate errors particularly to the level of edges. We aim to improve the analysis of networks of biological molecules by deriving modules together with edge relevance estimations that are based on global network characteristics. The key challenge we address here is investigating the capability of stochastic block models (SBMs) for representing and analyzing different types of biomolecular networks. Fitting them to SBMs both delivers modules of the networks and enables the derivation of edge confidence scores, and it has not yet been investigated for analyzing biomolecular networks. We apply SBM-based analysis independently to three correlation-based networks of breast cancer data originating from high-throughput measurements of different molecular layers: either transcriptomics, proteomics, or metabolomics. The networks were reduced by thresholding for correlation significance or by requirements on scale-freeness.  We find that the networks are best represented by the hierarchical version of the SBM, and many of the predicted blocks have a biologically and phenotypically relevant functional annotation. The edge confidence scores are overall in concordance with the biological evidence given by the measurements. We conclude that biomolecular networks can be appropriately represented and analyzed by fitting SBMs. As the SBM-derived edge confidence scores are based on global network connectivity characteristics and potential hierarchies within the biomolecular networks are considered, they could be used as additional, integrated features in network-based data comparisons.
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http://dx.doi.org/10.12688/f1000research.18705.2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6743255PMC
June 2020

Of Gene Expression and Cell Division Time: A Mathematical Framework for Advanced Differential Gene Expression and Data Analysis.

Cell Syst 2019 12 11;9(6):569-579.e7. Epub 2019 Sep 11.

Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Robert-Rössle-Str. 10, 13125 Berlin, Germany; Integrative Research Institute for the Life Sciences, Humboldt University Berlin, Philippstr. 13, 10115 Berlin, Germany. Electronic address:

Estimating fold changes of average mRNA and protein molecule counts per cell is the most common way to perform differential expression analysis. However, these gene expression data may be affected by cell division, an often-neglected phenomenon. Here, we develop a quantitative framework that links population-based mRNA and protein measurements to rates of gene expression in single cells undergoing cell division. The equations we derive are easy-to-use and widely robust against biological variability. They integrate multiple "omics" data into a coherent, quantitative description of single-cell gene expression and improve analysis when comparing systems or states with different cell division times. We explore these ideas in the context of resting versus activated B cells. Analyzing differences in protein synthesis rates enables to account for differences in cell division times. We demonstrate that this improves the resolution and hit rate of differential gene expression analysis when compared to analyzing population protein abundances alone.
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http://dx.doi.org/10.1016/j.cels.2019.07.009DOI Listing
December 2019

PRISMA: Protein Interaction Screen on Peptide Matrix Reveals Interaction Footprints and Modifications- Dependent Interactome of Intrinsically Disordered C/EBPβ.

iScience 2019 Mar 1;13:351-370. Epub 2019 Mar 1.

Max Delbrück Center for Molecular Medicine, Robert-Roessle Strasse 10, 13125 Berlin, Germany; Humboldt-University of Berlin, Institute of Biology, 10115 Berlin, Germany. Electronic address:

CCAAT enhancer-binding protein beta (C/EBPβ) is a pioneer transcription factor that specifies cell differentiation. C/EBPβ is intrinsically unstructured, a molecular feature common to many proteins involved in signal processing and epigenetics. The structure of C/EBPβ differs depending on alternative translation initiation and multiple post-translational modifications (PTM). Mutation of distinct PTM sites in C/EBPβ alters protein interactions and cell differentiation, suggesting that a C/EBPβ PTM indexing code determines epigenetic outcomes. Herein, we systematically explored the interactome of C/EBPβ using an array technique based on spot-synthesized C/EBPβ-derived linear tiling peptides with and without PTM, combined with mass spectrometric proteomic analysis of protein interactions. We identified interaction footprints of ∼1,300 proteins in nuclear extracts, many with chromatin modifying, chromatin remodeling, and RNA processing functions. The results suggest that C/EBPβ acts as a multi-tasking molecular switchboard, integrating signal-dependent modifications and structural plasticity to orchestrate interactions with numerous protein complexes directing cell fate and function.
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http://dx.doi.org/10.1016/j.isci.2019.02.026DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6424098PMC
March 2019

Integrated analysis of relapsed B-cell precursor Acute Lymphoblastic Leukemia identifies subtype-specific cytokine and metabolic signatures.

Sci Rep 2019 03 12;9(1):4188. Epub 2019 Mar 12.

Charité, University Hospital Berlin, Campus Benjamin Franklin, Department of Hematology and Oncology, Berlin, Germany.

Recent efforts reclassified B-Cell Precursor Acute Lymphoblastic Leukemia (BCP-ALL) into more refined subtypes. Nevertheless, outcomes of relapsed BCP-ALL remain unsatisfactory, particularly in adult patients where the molecular basis of relapse is still poorly understood. To elucidate the evolution of relapse in BCP-ALL, we established a comprehensive multi-omics dataset including DNA-sequencing, RNA-sequencing, DNA methylation array and proteome MASS-spec data from matched diagnosis and relapse samples of BCP-ALL patients (n = 50) including the subtypes DUX4, Ph-like and two aneuploid subtypes. Relapse-specific alterations were enriched for chromatin modifiers, nucleotide and steroid metabolism including the novel candidates FPGS, AGBL and ZNF483. The proteome expression analysis unraveled deregulation of metabolic pathways at relapse including the key proteins G6PD, TKT, GPI and PGD. Moreover, we identified a novel relapse-specific gene signature specific for DUX4 BCP-ALL patients highlighting chemotaxis and cytokine environment as a possible driver event at relapse. This study presents novel insights at distinct molecular levels of relapsed BCP-ALL based on a comprehensive multi-omics integrated data set including a valuable proteomics data set. The relapse specific aberrations reveal metabolic signatures on genomic and proteomic levels in BCP-ALL relapse. Furthermore, the chemokine expression signature in DUX4 relapse underscores the distinct status of DUX4-fusion BCP-ALL.
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http://dx.doi.org/10.1038/s41598-019-40786-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6414622PMC
March 2019

Self-assembly of Mutant Huntingtin Exon-1 Fragments into Large Complex Fibrillar Structures Involves Nucleated Branching.

J Mol Biol 2018 06 28;430(12):1725-1744. Epub 2018 Mar 28.

Neuroproteomics, Max Delbrueck Center for Molecular Medicine, Robert-Rössle-Straße 10, 13125 Berlin, Germany. Electronic address:

Huntingtin (HTT) fragments with extended polyglutamine tracts self-assemble into amyloid-like fibrillar aggregates. Elucidating the fibril formation mechanism is critical for understanding Huntington's disease pathology and for developing novel therapeutic strategies. Here, we performed systematic experimental and theoretical studies to examine the self-assembly of an aggregation-prone N-terminal HTT exon-1 fragment with 49 glutamines (Ex1Q49). Using high-resolution imaging techniques such as electron microscopy and atomic force microscopy, we show that Ex1Q49 fragments in cell-free assays spontaneously convert into large, highly complex bundles of amyloid fibrils with multiple ends and fibril branching points. Furthermore, we present experimental evidence that two nucleation mechanisms control spontaneous Ex1Q49 fibrillogenesis: (1) a relatively slow primary fibril-independent nucleation process, which involves the spontaneous formation of aggregation-competent fibrillary structures, and (2) a fast secondary fibril-dependent nucleation process, which involves nucleated branching and promotes the rapid assembly of highly complex fibril bundles with multiple ends. The proposed aggregation mechanism is supported by studies with the small molecule O4, which perturbs early events in the aggregation cascade and delays Ex1Q49 fibril assembly, comprehensive mathematical and computational modeling studies, and seeding experiments with small, preformed fibrillar Ex1Q49 aggregates that promote the assembly of amyloid fibrils. Together, our results suggest that nucleated branching in vitro plays a critical role in the formation of complex fibrillar HTT exon-1 aggregates with multiple ends.
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http://dx.doi.org/10.1016/j.jmb.2018.03.017DOI Listing
June 2018

Feedback, Mass Conservation and Reaction Kinetics Impact the Robustness of Cellular Oscillations.

PLoS Comput Biol 2016 Dec 27;12(12):e1005298. Epub 2016 Dec 27.

Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany.

Oscillations occur in a wide variety of cellular processes, for example in calcium and p53 signaling responses, in metabolic pathways or within gene-regulatory networks, e.g. the circadian system. Since it is of central importance to understand the influence of perturbations on the dynamics of these systems a number of experimental and theoretical studies have examined their robustness. The period of circadian oscillations has been found to be very robust and to provide reliable timing. For intracellular calcium oscillations the period has been shown to be very sensitive and to allow for frequency-encoded signaling. We here apply a comprehensive computational approach to study the robustness of period and amplitude of oscillatory systems. We employ different prototype oscillator models and a large number of parameter sets obtained by random sampling. This framework is used to examine the effect of three design principles on the sensitivities towards perturbations of the kinetic parameters. We find that a prototype oscillator with negative feedback has lower period sensitivities than a prototype oscillator relying on positive feedback, but on average higher amplitude sensitivities. For both oscillator types, the use of Michaelis-Menten instead of mass action kinetics in all degradation and conversion reactions leads to an increase in period as well as amplitude sensitivities. We observe moderate changes in sensitivities if replacing mass conversion reactions by purely regulatory reactions. These insights are validated for a set of established models of various cellular rhythms. Overall, our work highlights the importance of reaction kinetics and feedback type for the variability of period and amplitude and therefore for the establishment of predictive models.
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http://dx.doi.org/10.1371/journal.pcbi.1005298DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5226835PMC
December 2016

Quantitative dissection and modeling of the NF-κB p100-p105 module reveals interdependent precursor proteolysis.

Cell Rep 2014 Dec 4;9(5):1756-1769. Epub 2014 Dec 4.

Signal Transduction Laboratory, Max Delbrück Center for Molecular Medicine, Robert-Rössle-Strasse 10, 13125 Berlin, Germany. Electronic address:

The mechanisms that govern proteolytic maturation or complete destruction of the precursor proteins p100 and p105 are fundamental to homeostasis and activation of NF-κB; however, they remain poorly understood. Using mass-spectrometry-based quantitative analysis of noncanonical LTβR-induced signaling, we demonstrate that stimulation induces simultaneous processing of both p100 and p105. The precursors not only form hetero-oligomers but also interact with the ATPase VCP/p97, and their induced proteolysis strictly depends on the signal response domain (SRD) of p100, suggesting that the SRD-targeting proteolytic machinery acts in cis and in trans. Separation of cellular pools by isotope labeling revealed synchronous dynamics of p105 and p100 proteolysis. The generation of p50 and p52 from their precursors depends on functional VCP/p97. We have developed quantitative mathematical models that describe the dynamics of the system and predict that p100-p105 complexes are signal responsive.
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http://dx.doi.org/10.1016/j.celrep.2014.11.014DOI Listing
December 2014

Quantitative modelling of amyloidogenic processing and its influence by SORLA in Alzheimer's disease.

EMBO J 2012 Jan 11;31(1):187-200. Epub 2011 Oct 11.

Max-Delbrück-Center for Molecular Medicine, Berlin, Germany.

The extent of proteolytic processing of the amyloid precursor protein (APP) into neurotoxic amyloid-β (Aβ) peptides is central to the pathology of Alzheimer's disease (AD). Accordingly, modifiers that increase Aβ production rates are risk factors in the sporadic form of AD. In a novel systems biology approach, we combined quantitative biochemical studies with mathematical modelling to establish a kinetic model of amyloidogenic processing, and to evaluate the influence by SORLA/SORL1, an inhibitor of APP processing and important genetic risk factor. Contrary to previous hypotheses, our studies demonstrate that secretases represent allosteric enzymes that require cooperativity by APP oligomerization for efficient processing. Cooperativity enables swift adaptive changes in secretase activity with even small alterations in APP concentration. We also show that SORLA prevents APP oligomerization both in cultured cells and in the brain in vivo, eliminating the preferred form of the substrate and causing secretases to switch to a less efficient non-allosteric mode of action. These data represent the first mathematical description of the contribution of genetic risk factors to AD substantiating the relevance of subtle changes in SORLA levels for amyloidogenic processing as proposed for patients carrying SORL1 risk alleles.
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http://dx.doi.org/10.1038/emboj.2011.352DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3252570PMC
January 2012