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  • 1
    Book
    Book
    Systems-biological approach to Ras-mediated signal transduction / (2006)
    Berlin :Logos,
    Details
    UID:
    almahu_BV022217872
    Format: III, 182 S. : , Ill., graph. Darst.
    ISBN: 3-8325-1346-9
    Note: zugl.: Berlin, Humboldt-Univ., Diss., 2006
    Language: English
    Subjects: Biology
    RVK:
    WE 5320
    RVK:
    WG 3700
    Keywords: Signaltransduktion ; Ras-Proteine ; Systembiologie ; Hochschulschrift ; Hochschulschrift
    Author information: Blüthgen, Nils 1976-
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  • 2
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    Online Resource
    How scaffolds shape MAPK signaling: what we know and opportunities for systems approaches (2012)
    Berlin : Humboldt-Universität zu Berlin
    Details
    UID:
    edochu_18452_21763
    Format: 1 Online-Ressource (14 Seiten)
    Content: Scaffolding proteins add a new layer of complexity to the dynamics of cell signaling. Above their basic function to bring several components of a signaling pathway together, recent experimental research has found that scaffolds influence signaling in a much more complex way: scaffolds can exert some catalytic function, influence signaling by allosteric mechanisms, are feedback-regulated, localize signaling activity to distinct regions of the cell or increase pathway fidelity. Here we review experimental and theoretical approaches that address the function of two MAPK scaffolds, Ste5, a scaffold of the yeast mating pathway and KSR1/2, a scaffold of the classical mammalian MAPK signaling pathway. For the yeast scaffold Ste5, detailed mechanistic models have been valuable for the understanding of its function. For scaffolds in mammalian signaling, however, models have been rather generic and sketchy. For example, these models predicted narrow optimal scaffold concentrations, but when revisiting these models by assuming typical concentrations, rather a range of scaffold levels optimally supports signaling. Thus, more realistic models are needed to understand the role of scaffolds in mammalian signal transduction, which opens a big opportunity for systems biology.
    Content: Peer Reviewed
    In: Frontiers in Physiology, Lausanne : Frontiers Media S.A., 3,2012
    Language: English
    DOI: 10.3389/fphys.2012.00475
    DOI: 10.18452/21006
    URN: urn:nbn:de:kobv:11-110-18452/21763-7
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  • 3
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    Online Resource
    Neuronal activity regulates alternative exon usage (2020)
    Berlin : Humboldt-Universität zu Berlin
    Details
    UID:
    edochu_18452_27047
    Format: 1 Online-Ressource (24 Seiten)
    Content: Neuronal activity-regulated gene transcription underlies plasticity-dependent changes in the molecular composition and structure of neurons. A large number of genes regulated by different neuronal plasticity inducing pathways have been identified, but altered gene expression levels represent only part of the complexity of the activity-regulated transcriptional program. Alternative splicing, the differential inclusion and exclusion of exonic sequence in mRNA, is an additional mechanism that is thought to define the activity-dependent transcriptome. Here, we present a genome wide microarray-based survey to identify exons with increased expression levels at 1, 4 or 8 h following neuronal activity in the murine hippocampus provoked by generalized seizures. We used two different bioinformatics approaches to identify alternative activity-induced exon usage and to predict alternative splicing, ANOSVA (ANalysis Of Splicing VAriation) which we here adjusted to accommodate data from different time points and FIRMA (Finding Isoforms using Robust Multichip Analysis). RNA sequencing, in situ hybridization and reverse transcription PCR validate selected activity-dependent splicing events of previously described and so far undescribed activity-regulated transcripts, including Homer1a, Homer1d, Ania3, Errfi1, Inhba, Dclk1, Rcan1, Cda, Tpm1 and Krt75. Taken together, our survey significantly adds to the comprehensive understanding of the complex activity-dependent neuronal transcriptomic signature. In addition, we provide data sets that will serve as rich resources for future comparative expression analyses.
    Content: Peer Reviewed
    In: London : BioMed Central, 13,1
    Language: English
    DOI: 10.1186/s13041-020-00685-3
    DOI: 10.18452/26363
    URN: urn:nbn:de:kobv:11-110-18452/27047-3
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  • 4
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    In Silico Analysis Predicts Nuclear Factors NR2F6 and YAP1 as Mesenchymal Subtype-Specific Therapeutic Targets for Ovarian Cancer Patients (2023)
    Berlin : Humboldt-Universität zu Berlin
    Details
    UID:
    edochu_18452_27612
    Format: 1 Online-Ressource (20 Seiten)
    Content: Background: Tumour heterogeneity in high-grade serous ovarian cancer (HGSOC) is a proposed cause of acquired resistance to treatment and high rates of relapse. Among the four distinct molecular subtypes of HGSOC, the mesenchymal subtype (MES) has been observed with high frequency in several study cohorts. Moreover, it exhibits aggressive characteristics with poor prognosis. The failure to adequately exploit such subtypes for treatment results in high mortality rates, highlighting the need for effective targeted therapeutic strategies that follow the idea of personalized medicine (PM). Methods: As a proof-of-concept, bulk and single-cell RNA data were used to characterize the distinct composition of the tumour microenvironment (TME), as well as the cell–cell communication and its effects on downstream transcription of MES. Moreover, transcription factor activity contextualized with causal inference analysis identified novel therapeutic targets with potential causal impact on transcription factor dysregulation promoting the malignant phenotype. Findings: Fibroblast and macrophage phenotypes are of utmost importance for the complex intercellular crosstalk of MES. Specifically, tumour-associated macrophages were identified as the source of interleukin 1 beta (IL1B), a signalling molecule with significant impact on downstream transcription in tumour cells. Likewise, signalling molecules tumour necrosis factor (TNF), transforming growth factor beta (TGFB1), and C-X-C motif chemokine 12 (CXCL12) were prominent drivers of downstream gene expression associated with multiple cancer hallmarks. Furthermore, several consistently hyperactivated transcription factors were identified as potential sources for treatment opportunities. Finally, causal inference analysis identified Yes-associated protein 1 (YAP1) and Nuclear Receptor Subfamily 2 Group F Member 6 (NR2F6) as novel therapeutic targets in MES, verified in an independent dataset. Interpretation: By utilizing a sophisticated bioinformatics approach, several candidates for treatment opportunities, including YAP1 and NR2F6 were identified. These candidates represent signalling regulators within the cellular network of the MES. Hence, further studies to confirm these candidates as potential targeted therapies in PM are warranted.
    Content: Peer Reviewed
    In: Basel : MDPI, 15,12
    Language: English
    DOI: 10.3390/cancers15123155
    DOI: 10.18452/26919
    URN: urn:nbn:de:kobv:11-110-18452/27612-0
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  • 5
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    High Accuracy Classification of Developmental Toxicants by In Vitro Tests of Human Neuroepithelial and Cardiomyoblast Differentiation (2022)
    Berlin : Humboldt-Universität zu Berlin
    Details
    UID:
    edochu_18452_27136
    Format: 1 Online-Ressource (25 Seiten)
    Content: Human-relevant tests to predict developmental toxicity are urgently needed. A currently intensively studied approach makes use of differentiating human stem cells to measure chemically-induced deviations of the normal developmental program, as in a recent study based on cardiac differentiation (UKK2). Here, we (i) tested the performance of an assay modeling neuroepithelial differentiation (UKN1), and (ii) explored the benefit of combining assays (UKN1 and UKK2) that model different germ layers. Substance-induced cytotoxicity and genome-wide expression profiles of 23 teratogens and 16 non-teratogens at human-relevant concentrations were generated and used for statistical classification, resulting in accuracies of the UKN1 assay of 87–90%. A comparison to the UKK2 assay (accuracies of 90–92%) showed, in general, a high congruence in compound classification that may be explained by the fact that there was a high overlap of signaling pathways. Finally, the combination of both assays improved the prediction compared to each test alone, and reached accuracies of 92–95%. Although some compounds were misclassified by the individual tests, we conclude that UKN1 and UKK2 can be used for a reliable detection of teratogens in vitro, and that a combined analysis of tests that differentiate hiPSCs into different germ layers and cell types can even further improve the prediction of developmental toxicants.
    Content: Peer Reviewed
    In: Basel : MDPI, 11,21
    Language: English
    DOI: 10.3390/cells11213404
    DOI: 10.18452/26457
    URN: urn:nbn:de:kobv:11-110-18452/27136-7
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  • 6
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    A 3D gene expression atlas of the floral meristem based on spatial reconstruction of single nucleus RNA sequencing data (2022)
    Berlin : Humboldt-Universität zu Berlin
    Details
    UID:
    edochu_18452_26480
    Format: 1 Online-Ressource (11 Seiten)
    Content: Cellular heterogeneity in growth and differentiation results in organ patterning. Single-cell transcriptomics allows characterization of gene expression heterogeneity in developing organs at unprecedented resolution. However, the original physical location of the cell is lost during this methodology. To recover the original location of cells in the developing organ is essential to link gene activity with cellular identity and function in plants. Here, we propose a method to reconstruct genome-wide gene expression patterns of individual cells in a 3D flower meristem by combining single-nuclei RNA-seq with microcopy-based 3D spatial reconstruction. By this, gene expression differences among meristematic domains giving rise to different tissue and organ types can be determined. As a proof of principle, the method is used to trace the initiation of vascular identity within the floral meristem. Our work demonstrates the power of spatially reconstructed single cell transcriptome atlases to understand plant morphogenesis. The floral meristem 3D gene expression atlas can be accessed at http://threed-flower-meristem.herokuapp.com.
    Content: Peer Reviewed
    Note: This article was supported by the German Research Foundation (DFG) and the Open Access Publication Fund of Humboldt-Universität zu Berlin.
    In: [London] : Nature Publishing Group UK, 13
    Language: English
    DOI: 10.18452/25808
    DOI: 10.1038/s41467-022-30177-y
    URN: urn:nbn:de:kobv:11-110-18452/26480-2
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  • 7
    Book
    Book
    Systems biological approach to ras-mediated signal transduction / (2005)
    Berlin :Logos,
    Details
    UID:
    almafu_BV026580534
    Format: III, 180 S. : , Ill., graph. Darst.
    ISBN: 3-8325-1346-9
    Language: English
    Subjects: Biology
    RVK:
    WE 5320
    RVK:
    WG 3700
    Keywords: Signaltransduktion ; Ras-Proteine ; Systembiologie ; Hochschulschrift
    Author information: Blüthgen, Nils 1976-
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  • 8
    Book
    Book
    Systems-biological approach to Ras-mediated signal transduction / (2005)
    Details
    UID:
    almahu_BV025389346
    Format: 193 S. : , graph. Darst.
    Note: Berlin, Humboldt-Univ., Diss., 2005
    Language: English
    Subjects: Biology
    RVK:
    WE 5320
    RVK:
    WG 3700
    Keywords: Signaltransduktion ; Ras-Proteine ; Systembiologie ; Hochschulschrift
    Author information: Blüthgen, Nils, 1976-
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  • 9
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    Robust network inference using response logic (2019)
    Berlin : Humboldt-Universität zu Berlin
    Details
    UID:
    edochu_18452_29982
    Format: 1 Online-Ressource (9 Seiten)
    Content: Motivation A major challenge in molecular and cellular biology is to map out the regulatory networks of cells. As regulatory interactions can typically not be directly observed experimentally, various computational methods have been proposed to disentangling direct and indirect effects. Most of these rely on assumptions that are rarely met or cannot be adapted to a given context. Results We present a network inference method that is based on a simple response logic with minimal presumptions. It requires that we can experimentally observe whether or not some of the system’s components respond to perturbations of some other components, and then identifies the directed networks that most accurately account for the observed propagation of the signal. To cope with the intractable number of possible networks, we developed a logic programming approach that can infer networks of hundreds of nodes, while being robust to noisy, heterogeneous or missing data. This allows to directly integrate prior network knowledge and additional constraints such as sparsity. We systematically benchmark our method on KEGG pathways, and show that it outperforms existing approaches in DREAM3 and DREAM4 challenges. Applied to a novel perturbation dataset on PI3K and MAPK pathways in isogenic models of a colon cancer cell line, it generates plausible network hypotheses that explain distinct sensitivities toward various targeted inhibitors due to different PI3K mutants. Availability and implementation A Python/Answer Set Programming implementation can be accessed at github.com/GrossTor/response-logic. Data and analysis scripts are available at github.com/GrossTor/response-logic-projects. Supplementary information Supplementary data are available at Bioinformatics online.
    Content: Peer Reviewed
    In: Oxford : Oxford Univ. Press, 35,14, Seiten i634-i642
    Language: English
    DOI: 10.18452/29365
    DOI: 10.1093/bioinformatics/btz326
    URN: urn:nbn:de:kobv:11-110-18452/29982-8
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  • 10
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    Identifiability and experimental design in perturbation studies (2020)
    Berlin : Humboldt-Universität zu Berlin
    Details
    UID:
    edochu_18452_29983
    Format: 1 Online-Ressource (8 Seiten)
    Content: Motivation A common strategy to infer and quantify interactions between components of a biological system is to deduce them from the network’s response to targeted perturbations. Such perturbation experiments are often challenging and costly. Therefore, optimizing the experimental design is essential to achieve a meaningful characterization of biological networks. However, it remains difficult to predict which combination of perturbations allows to infer specific interaction strengths in a given network topology. Yet, such a description of identifiability is necessary to select perturbations that maximize the number of inferable parameters. Results We show analytically that the identifiability of network parameters can be determined by an intuitive maximum-flow problem. Furthermore, we used the theory of matroids to describe identifiability relationships between sets of parameters in order to build identifiable effective network models. Collectively, these results allowed to device strategies for an optimal design of the perturbation experiments. We benchmarked these strategies on a database of human pathways. Remarkably, full network identifiability was achieved, on average, with less than a third of the perturbations that are needed in a random experimental design. Moreover, we determined perturbation combinations that additionally decreased experimental effort compared to single-target perturbations. In summary, we provide a framework that allows to infer a maximal number of interaction strengths with a minimal number of perturbation experiments. Availability and implementation IdentiFlow is available at github.com/GrossTor/IdentiFlow. Supplementary information Supplementary data are available at Bioinformatics online.
    Content: Peer Reviewed
    In: Oxford : Oxford Univ. Press, 36,Supplement_1, Seiten i482-i489
    Language: English
    DOI: 10.18452/29366
    DOI: 10.1093/bioinformatics/btaa404
    URN: urn:nbn:de:kobv:11-110-18452/29983-4
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