Theodor-Boveri-Institut für Biowissenschaften
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- Lehrstuhl für Tissue Engineering und Regenerative Medizin (18) (remove)
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The signal modelling framework JimenaE simulates dynamically Boolean networks. In contrast to SQUAD, there is systematic and not just heuristic calculation of all system states. These specific features are not present in CellNetAnalyzer and BoolNet. JimenaE is an expert extension of Jimena, with new optimized code, network conversion into different formats, rapid convergence both for system state calculation as well as for all three network centralities. It allows higher accuracy in determining network states and allows to dissect networks and identification of network control type and amount for each protein with high accuracy. Biological examples demonstrate this: (i) High plasticity of mesenchymal stromal cells for differentiation into chondrocytes, osteoblasts and adipocytes and differentiation-specific network control focusses on wnt-, TGF-beta and PPAR-gamma signaling. JimenaE allows to study individual proteins, removal or adding interactions (or autocrine loops) and accurately quantifies effects as well as number of system states. (ii) Dynamical modelling of cell–cell interactions of plant Arapidopsis thaliana against Pseudomonas syringae DC3000: We analyze for the first time the pathogen perspective and its interaction with the host. We next provide a detailed analysis on how plant hormonal regulation stimulates specific proteins and who and which protein has which type and amount of network control including a detailed heatmap of the A.thaliana response distinguishing between two states of the immune response. (iii) In an immune response network of dendritic cells confronted with Aspergillus fumigatus, JimenaE calculates now accurately the specific values for centralities and protein-specific network control including chemokine and pattern recognition receptors.
Infection research largely relies on classical cell culture or mouse models. Despite having delivered invaluable insights into host-pathogen interactions, both have limitations in translating mechanistic principles to human pathologies. Alternatives can be derived from modern Tissue Engineering approaches, allowing the reconstruction of functional tissue models in vitro. Here, we combined a biological extracellular matrix with primary tissue-derived enteroids to establish an in vitro model of the human small intestinal epithelium exhibiting in vivo-like characteristics. Using the foodborne pathogen Salmonella enterica serovar Typhimurium, we demonstrated the applicability of our model to enteric infection research in the human context. Infection assays coupled to spatio-temporal readouts recapitulated the established key steps of epithelial infection by this pathogen in our model. Besides, we detected the upregulation of olfactomedin 4 in infected cells, a hitherto unrecognized aspect of the host response to Salmonella infection. Together, this primary human small intestinal tissue model fills the gap between simplistic cell culture and animal models of infection, and shall prove valuable in uncovering human-specific features of host-pathogen interplay.
Ovarian cancer is the second most common gynecological malignancy in women. More than 70% of the cases are diagnosed at the advanced stage, presenting as primary peritoneal metastasis, which results in a poor 5-year survival rate of around 40%. Mechanisms of peritoneal metastasis, including adhesion, migration, and invasion, are still not completely understood and therapeutic options are extremely limited. Therefore, there is a strong requirement for a 3D model mimicking the in vivo situation. In this study, we describe the establishment of a 3D tissue model of the human peritoneum based on decellularized porcine small intestinal submucosa (SIS) scaffold. The SIS scaffold was populated with human dermal fibroblasts, with LP-9 cells on the apical side representing the peritoneal mesothelium, while HUVEC cells on the basal side of the scaffold served to mimic the endothelial cell layer. Functional analyses of the transepithelial electrical resistance (TEER) and the FITC-dextran assay indicated the high barrier integrity of our model. The histological, immunohistochemical, and ultrastructural analyses showed the main characteristics of the site of adhesion. Initial experiments using the SKOV-3 cell line as representative for ovarian carcinoma demonstrated the usefulness of our models for studying tumor cell adhesion, as well as the effect of tumor cells on endothelial cell-to-cell contacts. Taken together, our data show that the novel peritoneal 3D tissue model is a promising tool for studying the peritoneal dissemination of ovarian cancer.
Epithelial-to-mesenchymal transition (EMT) is discussed to be centrally involved in invasion, stemness, and drug resistance. Experimental models to evaluate this process in its biological complexity are limited. To shed light on EMT impact and test drug response more reliably, we use a lung tumor test system based on a decellularized intestinal matrix showing more in vivo-like proliferation levels and enhanced expression of clinical markers and carcinogenesis-related genes. In our models, we found evidence for a correlation of EMT with drug resistance in primary and secondary resistant cells harboring KRAS\(^{G12C}\) or EGFR mutations, which was simulated in silico based on an optimized signaling network topology. Notably, drug resistance did not correlate with EMT status in KRAS-mutated patient-derived xenograft (PDX) cell lines, and drug efficacy was not affected by EMT induction via TGF-β. To investigate further determinants of drug response, we tested several drugs in combination with a KRAS\(^{G12C}\) inhibitor in KRAS\(^{G12C}\) mutant HCC44 models, which, besides EMT, display mutations in P53, LKB1, KEAP1, and high c-MYC expression. We identified an aurora-kinase A (AURKA) inhibitor as the most promising candidate. In our network, AURKA is a centrally linked hub to EMT, proliferation, apoptosis, LKB1, and c-MYC. This exemplifies our systemic analysis approach for clinical translation of biomarker signatures.
A fine balance of regulatory (T\(_{reg}\)) and conventional CD4\(^+\) T cells (T\(_{conv}\)) is required to prevent harmful immune responses, while at the same time ensuring the development of protective immunity against pathogens. As for many cellular processes, sphingolipid metabolism also crucially modulates the T\(_{reg}\)/T\(_{conv}\) balance. However, our understanding of how sphingolipid metabolism is involved in T cell biology is still evolving and a better characterization of the tools at hand is required to advance the field. Therefore, we established a reductionist liposomal membrane model system to imitate the plasma membrane of mouse T\(_{reg}\) and T\(_{conv}\) with regards to their ceramide content. We found that the capacity of membranes to incorporate externally added azide-functionalized ceramide positively correlated with the ceramide content of the liposomes. Moreover, we studied the impact of the different liposomal preparations on primary mouse splenocytes in vitro. The addition of liposomes to resting, but not activated, splenocytes maintained viability with liposomes containing high amounts of C\(_{16}\)-ceramide being most efficient. Our data thus suggest that differences in ceramide post-incorporation into T\(_{reg}\) and T\(_{conv}\) reflect differences in the ceramide content of cellular membranes.
High attrition-rates entailed by drug testing in 2D cell culture and animal models stress the need for improved modeling of human tumor tissues. In previous studies our 3D models on a decellularized tissue matrix have shown better predictivity and higher chemoresistance. A single porcine intestine yields material for 150 3D models of breast, lung, colorectal cancer (CRC) or leukemia. The uniquely preserved structure of the basement membrane enables physiological anchorage of endothelial cells and epithelial-derived carcinoma cells. The matrix provides different niches for cell growth: on top as monolayer, in crypts as aggregates and within deeper layers. Dynamic culture in bioreactors enhances cell growth. Comparing gene expression between 2D and 3D cultures, we observed changes related to proliferation, apoptosis and stemness. For drug target predictions, we utilize tumor-specific sequencing data in our in silico model finding an additive effect of metformin and gefitinib treatment for lung cancer in silico, validated in vitro. To analyze mode-of-action, immune therapies such as trispecific T-cell engagers in leukemia, as well as toxicity on non-cancer cells, the model can be modularly enriched with human endothelial cells (hECs), immune cells and fibroblasts. Upon addition of hECs, transmigration of immune cells through the endothelial barrier can be investigated. In an allogenic CRC model we observe a lower basic apoptosis rate after applying PBMCs in 3D compared to 2D, which offers new options to mirror antigen-specific immunotherapies in vitro. In conclusion, we present modular human 3D tumor models with tissue-like features for preclinical testing to reduce animal experiments.
To study the interaction of human pathogens with their host target structures, human tissue models based on primary cells are considered suitable. Complex tissue models of the human airways have been used as infection models for various viral and bacterial pathogens. The Gram-negative bacterium Bordetella pertussis is of relevant clinical interest since whooping cough has developed into a resurgent infectious disease. In the present study, we created three-dimensional tissue models of the human ciliated nasal and tracheo-bronchial mucosa. We compared the innate immune response of these models towards the B. pertussis virulence factor adenylate cyclase toxin (CyaA) and its enzymatically inactive but fully pore-forming toxoid CyaA-AC\(^-\). Applying molecular biological, histological, and microbiological assays, we found that 1 µg/ml CyaA elevated the intracellular cAMP level but did not disturb the epithelial barrier integrity of nasal and tracheo-bronchial airway mucosa tissue models. Interestingly, CyaA significantly increased interleukin 6, interleukin 8, and human beta defensin 2 secretion in nasal tissue models, whereas tracheo-bronchial tissue models were not significantly affected compared to the controls. Subsequently, we investigated the interaction of B. pertussis with both differentiated primary nasal and tracheo-bronchial tissue models and demonstrated bacterial adherence and invasion without observing host cell type-specific significant differences. Even though the nasal and the tracheo-bronchial mucosa appear similar from a histological perspective, they are differentially susceptible to B. pertussis CyaA in vitro. Our finding that nasal tissue models showed an increased innate immune response towards the B. pertussis virulence factor CyaA compared to tracheo-bronchial tissue models may reflect the key role of the nasal airway mucosa as the first line of defense against airborne pathogens.
Activity of Tracheal Cytotoxin of Bordetella pertussis in a Human Tracheobronchial 3D Tissue Model
(2021)
Bordetella pertussis is a highly contagious pathogen which causes whooping cough in humans. A major pathophysiology of infection is the extrusion of ciliated cells and subsequent disruption of the respiratory mucosa. Tracheal cytotoxin (TCT) is the only virulence factor produced by B. pertussis that has been able to recapitulate this pathology in animal models. This pathophysiology is well characterized in a hamster tracheal model, but human data are lacking due to scarcity of donor material. We assessed the impact of TCT and lipopolysaccharide (LPS) on the functional integrity of the human airway mucosa by using in vitro airway mucosa models developed by co-culturing human tracheobronchial epithelial cells and human tracheobronchial fibroblasts on porcine small intestinal submucosa scaffold under airlift conditions. TCT and LPS either alone and in combination induced blebbing and necrosis of the ciliated epithelia. TCT and LPS induced loss of ciliated epithelial cells and hyper-mucus production which interfered with mucociliary clearance. In addition, the toxins had a disruptive effect on the tight junction organization, significantly reduced transepithelial electrical resistance and increased FITC-Dextran permeability after toxin incubation. In summary, the results indicate that TCT collaborates with LPS to induce the disruption of the human airway mucosa as reported for the hamster tracheal model.
Gonorrhea, a sexually transmitted disease caused by the bacteria Neisseria gonorrhoeae, is characterized by a large number of neutrophils recruited to the site of infection. Therefore, proper modeling of the N. gonorrhoeae interaction with neutrophils is very important for investigating and understanding the mechanisms that gonococci use to evade the immune response. We have used a combination of a unique human 3D tissue model together with a dynamic culture system to study neutrophil transmigration to the site of N. gonorrhoeae infection. The triple co-culture model consisted of epithelial cells (T84 human colorectal carcinoma cells), human primary dermal fibroblasts, and human umbilical vein endothelial cells on a biological scaffold (SIS). After the infection of the tissue model with N. gonorrhoeae, we introduced primary human neutrophils to the endothelial side of the model using a perfusion-based bioreactor system. By this approach, we were able to demonstrate the activation and transmigration of neutrophils across the 3D tissue model and their recruitment to the site of infection. In summary, the triple co-culture model supplemented by neutrophils represents a promising tool for investigating N. gonorrhoeae and other bacterial infections and interactions with the innate immunity cells under conditions closely resembling the native tissue environment.
To improve and focus preclinical testing, we combine tumor models based on a decellularized tissue matrix with bioinformatics to stratify tumors according to stage-specific mutations that are linked to central cancer pathways. We generated tissue models with BRAF-mutant colorectal cancer (CRC) cells (HROC24 and HROC87) and compared treatment responses to two-dimensional (2D) cultures and xenografts. As the BRAF inhibitor vemurafenib is—in contrast to melanoma—not effective in CRC, we combined it with the EGFR inhibitor gefitinib. In general, our 3D models showed higher chemoresistance and in contrast to 2D a more active HGFR after gefitinib and combination-therapy. In xenograft models murine HGF could not activate the human HGFR, stressing the importance of the human microenvironment. In order to stratify patient groups for targeted treatment options in CRC, an in silico topology with different stages including mutations and changes in common signaling pathways was developed. We applied the established topology for in silico simulations to predict new therapeutic options for BRAF-mutated CRC patients in advanced stages. Our in silico tool connects genome information with a deeper understanding of tumor engines in clinically relevant signaling networks which goes beyond the consideration of single drivers to improve CRC patient stratification.