The EMT transcription factor Zeb2 controls adult murine hematopoietic differentiation by regulating cytokine signaling.

Epithelial-to-mesenchymal-transition (EMT) is critical for normal embryogenesis and effective postnatal wound healing, but is also associated with cancer metastasis. SNAIL, ZEB, and TWIST families of transcription factors are key modulators of the EMT process, but their precise roles in adult hematopoietic development and homeostasis remain unclear. Here we report that genetic inactivation of Zeb2 results in increased frequency of stem and progenitor subpopulations within the bone marrow (BM) and spleen and that these changes accompany differentiation defects in multiple hematopoietic cell lineages. We found no evidence that Zeb2 is critical for hematopoietic stem cell self-renewal capacity. However, knocking out Zeb2 in the BM promoted a phenotype with several features that resemble human myeloproliferative disorders, such as BM fibrosis, splenomegaly, and extramedullary hematopoiesis. Global gene expression and intracellular signal transduction analysis revealed perturbations in specific cytokine and cytokine receptor-related signaling pathways following Zeb2 loss, especially the JAK-STAT and extracellular signal-regulated kinase pathways. Moreover, we detected some previously unknown mutations within the human Zeb2 gene (ZFX1B locus) from patients with myeloid disease. Collectively, our results demonstrate that Zeb2 controls adult hematopoietic differentiation and lineage fidelity through widespread modulation of dominant signaling pathways that may contribute to blood disorders.

Defining a Characteristic Gene Expression Set Responsible for Cancer Stem Cell-Like Features in a Sub-Population of Ewing Sarcoma Cells CADO-ES1.

One of the still open questions in Ewing sarcoma, a rare bone tumor with weak therapeutic options, is to identify the tumor-driving cell (sub) population and to understand the specifics in the biological network of these cells. This basic scientific insight might foster the development of more specific therapeutic target patterns. The experimental approach is based on a side population (SP) of Ewing cells, based on the model cell line CADO-ES1. The SP is established by flow cytometry and defined by the idea that tumor stem-like cells can be identified by the time-course in clearing a given artificial dye. The SP was characterized by a higher colony forming activity, by a higher differentiation potential, by higher resistance to cytotoxic drugs, and by morphology. Several SP and non-SP cell fractions and bone marrow-derived mesenchymal stem cell reference were analyzed by short read sequencing of the full transcriptome. The double-differential analysis leads to an altered expression structure of SP cells centered around the AP-1 and APC/c complex. The SP cells share only a limited proportion of the full mesenchymal stem cell stemness set of genes. This is in line with the expectation that tumor stem-like cells share only a limited subset of stemness features which are relevant for tumor survival.

Charge Polarity Control in Organic Transistors of Mixed and Segregated Complexes Based on Diaminonaphthalene and Pyrene.

Organic cocrystals of diaminonaphthalene (DAN) and diaminopyrene (DAP) with bromanil (BA) and tetracyanoquinodimethane (TCNQ) are an exemplar system for understanding the charge-transport process, where from the viewpoint of partition theory, orbital symmetry plays a crucial role in controlling the carrier charge polarity of transistors. In the mixed-stack complexes of BA and other p-quinone acceptors, a comparatively weak donor, 1,5-DAN, shows p-channel characteristics owing to the counteractive contribution of the next highest occupied molecular orbital for electron transport. This characteristic behavior occurs because the BA molecule, situated on top of the amino group, overlaps with half of the DAN molecule. By contrast, the BA and TCNQ complexes of a stronger donor, 1,6-DAP, exhibit n-channel transport due to the cooperative path and orthogonal orbitals. Similarly, TCNQ complexes of variously substituted DAN show n-channel transport, where the TCNQ molecules are located on top of the DAN molecules. However, when the carbon electrodes of (1,5-DAN)(BA) are replaced by silver, electron transport appears due to the competitive effect of the Schottky barriers. In a highly conducting segregated complex of (1,6-DAP)(TCNQ), ambipolar transistor characteristics are observed without subtracting the bulk current by using carefully prepared thin-film transistors.

Target discovery screens using pooled shRNA libraries and next-generation sequencing: A model workflow and analytical algorithm.

In the search for novel therapeutic targets, RNA interference screening has become a valuable tool. High-throughput technologies are now broadly accessible but their assay development from baseline remains resource-intensive and challenging. Focusing on this assay development process, we here describe a target discovery screen using pooled shRNA libraries and next-generation sequencing (NGS) deconvolution in a cell line model of Ewing sarcoma. In a strategy designed for comparative and synthetic lethal studies, we screened for targets specific to the A673 Ewing sarcoma cell line. Methods, results and pitfalls are described for the entire multi-step screening procedure, from lentiviral shRNA delivery to bioinformatics analysis, illustrating a complete model workflow. We demonstrate that successful studies are feasible from the first assay performance and independent of specialized screening units. Furthermore, we show that a resource-saving screen depth of 100-fold average shRNA representation can suffice to generate reproducible target hits despite heterogeneity in the derived datasets. Because statistical analysis methods are debatable for such datasets, we created ProFED, an analysis package designed to facilitate descriptive data analysis and hit calling using an aim-oriented profile filtering approach. In its versatile design, this open-source online tool provides fast and easy analysis of shRNA and other count-based datasets to complement other analytical algorithms.

TMAinspiration: Decode Interdependencies in Multifactorial Tissue Microarray Data.

There are no satisfying tools in tissue microarray (TMA) data analysis up to now to analyze the cooperative behavior of all measured markers in a multifactorial TMA approach. The developed tool TMAinspiration is not only offering an analysis option to close this gap but also offering an ecosystem consisting of quality control concepts and supporting scripts to make this approach a platform for informed practice and further research. The TMAinspiration method is specifically focusing on the demands of the TMA analysis by controlling errors and noise by a generalized regression scheme while at the same time avoiding to introduce a priori too many constraints into the analysis of the data. So, we are testing partitions of a proximity table to find an optimal support for a ranking scheme of molecular dependencies. The idea of combining several partitions to one ensemble, which is balancing the optimization process, is based on the main assumption that all these perspectives on the cellular network need to be self-consistent. Several application examples in breast cancer and one in squamous cell carcinoma demonstrate that this procedure is nicely confirming a priori knowledge on the expression characteristics of protein markers, while also integrating many new results discovered in the treasury of a bigger TMA experiment. The code and software are now freely available at: http://complex-systems.uni-muenster.de/tma_inspiration.html.

TGF-ß stimulation in human and murine cells reveals commonly affected biological processes and pathways at transcription level.

BACKGROUND: The TGF-ß signaling pathway is a fundamental pathway in the living cell, which plays a key role in many central cellular processes. The complex and sometimes contradicting mechanisms by which TGF-ß yields phenotypic effects are not yet completely understood. In this study we investigated and compared the transcriptional response profile of TGF-ß1 stimulation in different cell types. For this purpose, extensive experiments are performed and time-course microarray data are generated in human and mouse parenchymal liver cells, human mesenchymal stromal cells and mouse hematopoietic progenitor cells at different time points. We applied a panel of bioinformatics methods on our data to uncover common patterns in the dynamic gene expression response in respective cells. RESULTS: Our analysis revealed a quite variable and multifaceted transcriptional response profile of TGF-ß1 stimulation, which goes far beyond the well-characterized classical TGF-ß1 signaling pathway. Nonetheless, we could identify several commonly affected processes and signaling pathways across cell types and species. In addition our analysis suggested an important role of the transcription factor EGR1, which appeared to have a conserved influence across cell-types and species. Validation via an independent dataset on A549 lung adenocarcinoma cells largely confirmed our findings. Network analysis suggested explanations, how TGF-ß1 stimulation could lead to the observed effects. CONCLUSIONS: The analysis of dynamical transcriptional response to TGF-ß treatment experiments in different human and murine cell systems revealed commonly affected biological processes and pathways, which could be linked to TGF-ß1 via network analysis. This helps to gain insights about TGF-ß pathway activities in these cell systems and its conserved interactions between the species and tissue types.