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Additional file 5: Table S4. Genotyping primers used.

Additional file 33. Original blots corresponding to Additional Fig. S3 (panel A, left side): Southern blot analysis of ES cells successfully targeted with the Pcdh10all targeting construct.

Additional file 4: Fig. S3. Verification of targeted ES cells and recombinant Pcdh10allfl/fl and Pcdh10longfl/fl mice at the genomic level.

Additional file 6: Table S5. Primers used for quantitative RT-PCR.

Additional file 15: Table S11. Statistical analysis of Kaplan Meyer tumor-free curves for GFAP-Cre experiment.

Additional file 22: Table S14. Statistical analysis of allograft growth curves for PTD7, PTD25 and their Pcdh10-rescued derivative cell lines.

Additional file 26. Original uncropped blots corresponding to Fig. 3, panels A-D (Pcdh10 expression levels in Pcdh10all mice by Western blot analysis). Antibodies used are indicated at the left. Exposure time was 1 min.

Additional file 27. Original uncropped blots corresponding to Fig. 3, panels A-D (Pcdh10 expression levels in Pcdh10all−/− mice by Western blot analysis). Antibodies used are indicated at the left. Exposure time was 10 min.

Additional file 18: Table S12. Derivation and detailed analysis of pinnal-tumor derived (PTD) cell lines and rescued derivatives.

Additional file 8: Table S7. Protocadherin-10 specific antibodies used.

Additional file 32. Original uncropped blot corresponding to Fig. 4, panels A-D (Pcdh10 expression levels in Pcdh10long−/− mice by Western blot analysis). Antibody used in reprobing the blots was anti-beta-tubulin. Exposure time was 1 s.

Additional file 21: Fig. S11. Immunofluorescent detection of desmin in PTD cell cultures and derivatives.

Additional file 34. Original blots corresponding to Additional Fig. S3 (panel A, right side): Southern blot analysis of ES cells successfully targeted with the Pcdh10long targeting construct.

Additional file 16: Fig. S7. Examples of validation of antibody specifity in immunohistochemical detection of various antigens on mouse WT and tumoral tissues.

Additional file 28. Original uncropped blots corresponding to Fig. 3, panels A-D (Pcdh10 expression levels in Pcdh10all−/− mice by Western blot analysis). Antibody used in reprobing the blots was anti-beta-tubulin. Exposure time was 1 s.

Additional file 12: Fig. S4. mRNA expression levels of δ-Pcdhs in Pcdh10all−/− and Pcdh10long−/− mouse brains.

Additional file 19: Fig. S9. Allograft formation after s.c. injection of PTD single-cell suspensions into athymic nude mice.

Additional file 3: Table S3. Primers used for generation of Southern probes.

Additional file 24: comprising Figs. S12-S17. 24a: Fig. S12. Summary of differentially expressed (DE) genes in PTD7_RS (rescued by short isoform 1 of Pcdh10) versus malignant Pcdh10-lacking PTD7 cells. 24b: Fig. S13. Summary of DE genes in PTD25_RS (rescued by short isoform 1 of Pcdh10) versus malignant Pcdh10-lacking PTD25 cells. 24c: Fig. S14. Summary of DE genes in PTD25_RL (rescued by long isoform 4 of Pcdh10) versus malignant Pcdh10-lacking PTD25 cells. 24d: Fig. S15. Summary of DE genes shared by both PTD7_RS and PTD7_RL in comparison with malignant Pcdh10-lacking PTD7 cells. 24e: Fig. S16. Summary of DE genes shared by both PTD25_RS and PTD25_RL in comparison with malignant Pcdh10-lacking PTD25 cells. 24f: Fig. S17. Summary of DE genes in malignant Pcdh10-lacking PTD25 versus malignant Pcdh10-lacking PTD7 cells.

Additional file 7: Table S6. Primary antibodies used.

Additional file 13: Fig. S5. Phenotypic and reproduction data for Pcdh10all−/− and Pcdh10long−/− knockout (KO) mice.

Additional file 30. Original uncropped blot corresponding to Fig. 4, panels A-D (Pcdh10 expression levels in Pcdh10long−/− mice by Western blot analysis). Antibodies used are indicated at the left. Exposure time was 1 min.

Additional file 29. Original uncropped blot corresponding to Fig. 4, panels A-D (Pcdh10 expression levels in Pcdh10long−/− mice by Western blot analysis). Antibodies used are indicated at the left. Exposure time was 30 s.

Additional file 2. Strategy for conditional knockout of the long isoforms of the Pcdh10 allele. Includes textual description of the strategy, Fig. S2 (Schematic representation of the recombineering strategy of the Pcdh10long targeting construct) and Table S2 (Recombineering primers used for generation of the Pcdh10long targeting construct).

Additional file 14: Fig. S6. Body weight curves of Pcdh10all−/− and Pcdh10long−/− KO mice.

Additional file 31. Original uncropped blot corresponding to Fig. 4, panels A-D (Pcdh10 expression levels in Pcdh10long−/− mice by Western blot analysis). Antibodies used are indicated at the left. Exposure time was 5 min.

Additional file 1. Strategy for conditional knockout of all isoforms of the Pcdh10 allele. Includes textual description of the strategy, Fig. S1 (Schematic representation of the recombineering strategy of the Pcdh10all targeting construct) and Table S1 (Recombineering primers used for generation of the Pcdh10all targeting construct).

Additional file 17: Fig. S8. Immunohistochemical detection of E-cadherin and catenins in representative pinnal tumors.

Additional file 35. Animal Facility Procedures and Licenses of the VIB-UGent Center for Inflammation Research (IRC), Ghent, Belgium.

Additional file 25: Fig. S18. IPA-generated ‘Cell death and survival’ network of genes differentially expressed in PTD25_RS (rescued by short isoform 1 of Pcdh10) versus malignant Pcdh10-lacking PTD25 cells.

Additional file 20. Lung colonization assay for selected PTD cell lines. Includes Table S13 and Fig. S10.

Additional file 23: Table S15. Expression of 134 selected genes in PTD7, PTD25 and derivatives

Summary While components of the pathway that establishes left-right asymmetry have been identified in diverse animals, from vertebrates to flies, it is striking that the genes involved in the first symmetry-breaking step remain wholly unknown in the most obviously chiral animals, the gastropod snails. Previously, research on snails was used to show that left-right signaling of Nodal, downstream of symmetry breaking, may be an ancestral feature of the Bilateria [1, 2]. Here, we report that a disabling mutation in one copy of a tandemly duplicated, diaphanous-related formin is perfectly associated with symmetry breaking in the pond snail. This is supported by the observation that an anti-formin drug treatment converts dextral snail embryos to a sinistral phenocopy, and in frogs, drug inhibition or overexpression by microinjection of formin has a chirality-randomizing effect in early (pre-cilia) embryos. Contrary to expectations based on existing models [3, 4, 5], we discovered asymmetric gene expression in 2- and 4-cell snail embryos, preceding morphological asymmetry. As the formin-actin filament has been shown to be part of an asymmetry-breaking switch in vitro [6, 7], together these results are consistent with the view that animals with diverse body plans may derive their asymmetries from the same intracellular chiral elements [8]., Highlights • Animals tend to be outwardly symmetric but internally are asymmetric • Unlike other animals, snails show inherited variation in asymmetry • We found that both snails and frogs use a common gene to define left and right • Asymmetry is probably an ancient and conserved property of cells and animals, Davison et al. have discovered a cell scaffolding protein in snails and frogs that controls body asymmetry, either the direction a snail shell coils, or whether a frog heart is placed to the left or right. Body asymmetry in animals, including humans, likely arises from a highly conserved, intrinsic asymmetry of the cell.

International audience; In this study, we explore the role of the human NANOS3 germline gene in lung tumour progression. We report that Nanos3 is overexpressed by invasive lung cancer cells and represents a new prognostic marker for non-small cell lung carcinomas (NSCLC). We also show that Nanos3 gene expression is restricted in testis and brain and is regulated by epigenetic events. Moreover, we demonstrate that Nanos3 is upregulated in cultured cells undergoing epithelialmesenchymal transition (EMT). Nanos3 overexpression in human NSCLC cell lines enhances their invasiveness by upregulating EMT, whereas its silencing induces mesenchymalepithelial transition. Nanos3 represses E-cadherin at the transcriptional level and upregulates Vimentin post-transcriptionally. Also, we show that Nanos3 binds mRNAs encoding Vimentin and regulates the length of the 3' poly(A) tail of VIM mRNA Finally, Nanos3 can also protect Vimentin mRNA from microRNA-mediated repression. We thus demonstrate a new role for Nanos3 in the acquisition of invasiveness by human lung tumour cells and propose a new mechanism of post-transcriptional regulation of EMT.

no abstract available

Ovarian carcinoma arises from the ovarian surface epithelium, which undergoes phenotypic changes characteristic of müllerian epithelium during the first stages of tumorigenesis. The variant isoform of the hepatocyte nuclear factor 1 (vHNF1) is a transcription factor involved in the development of tissues derived from the müllerian duct. Here, we show that vHNF1 knockdown in two ovarian carcinoma cell lines, SKOV3 and IGROV1, leads to reduced E-cadherin (E-cadh) expression and decreased proliferation rate. Accordingly, SKOV3 cells ectopically expressing a dominant-negative (DN) vHNF1 mutant undergo an epithelial-mesenchymal-like transition, acquiring a spindle-like morphology, loss of E-cadh, and disrupted cell-cell contacts. Gene expression profiling of DNvHNF1 cells on the basis of a newly compiled list of epithelial-mesenchymal transition-related genes revealed a correlation between vHNF1 loss-of-function and acquisition of the mesenchymal phenotype. Indeed, phenotypic changes were associated with increased Slug transcription and functionality. Accordingly, vHNF1-transfected immortalized ovarian surface epithelial cells showed down-regulation of Snail and Slug transcripts. In DNvHNF1-transfected SKOV3 cells, growth rate decreased, and in vHNF1-transfected immortalized ovarian surface epithelial cells, growth rate increased. By immunohistochemistry, we found a strong association of vHNF1 with E-cadh in clear cell and in a subset of serous carcinomas, data that could potentially contribute in distinguishing different types of ovarian tumors. Our results may help in understanding the biology of ovarian carcinoma, identifying early detection markers, and opening potential avenues for therapeutic intervention.

Alpha-catenins play key functional roles in cadherin-catenin cell-cell adhesion complexes. We previously reported on alphaT-catenin, a novel member of the alpha-catenin protein family. alphaT-catenin is expressed predominantly in cardiomyocytes, where it colocalizes with alphaE-catenin at the intercalated discs. Whether alphaT- and alphaE-catenin have specific or synergistic functions remains unknown. In this study we used the yeast two-hybrid approach to identify specific functions of alphaT-catenin. An interaction between alphaT-catenin and plakophilins was observed and subsequently confirmed by co-immunoprecipitation and colocalization. Interaction with the amino-terminal part of plakophilins appeared to be specific for the central ;adhesion-modulation' domain of alphaT-catenin. In addition, we showed, by immuno-electron microscopy, that desmosomal proteins in the heart localize not only to the desmosomes in the intercalated discs but also at adhering junctions with hybrid composition. We found that in thelatter junctions, endogenous plakophilin-2 colocalizes with alphaT-catenin. By providing an extra link between the cadherin-catenin complex and intermediate filaments, the binding of alphaT-catenin to plakophilin-2 is proposed to be a means of modulating and strengthening cell-cell adhesion between cardiac muscle cells. This could explain the devastating effect of plakophilin-2 mutations on cell junction stability in intercalated discs, which lead to cardiac muscle malfunction.

Plakophilin 3 (PKP3) belongs to the p120ctn family of armadillo-related proteins predominantly functioning in desmosome formation. Here we report that PKP3 is transcriptionally repressed by the E-cadherin repressor ZEB1 in metastatic cancer cells. ZEB1 physically associates with two conserved Ebox elements in the PKP3 promoter and partially represses the activity of corresponding human and mouse PKP3 promoter fragments in reporter gene assays. In human tumours ZEB1 is upregulated in invasive cancer cells at the tumour/host interface, which is accompanied by downregulation of PKP3 expression levels. Hence, the transcriptional repression of PKP3 by ZEB1 contributes to ZEB1-mediated disintegration of intercellular adhesion and epithelial to mesenchymal transition.

We have constructed a 1.4-Mb P1 artificial chromosome/bacterial artificial chromosome (PAC/BAC) contig spanning the 17q breakpoint of a constitutional translocation t(1;17)(p36.2;q11.2) in a patient with neuroblastoma. Three 17q breakpoint-overlapping cosmids were identified and sequenced. No coding sequences were found in the immediate proximity of the 17q breakpoint. The PAC/BAC contig covers the region between the proximally located ACCN1 gene and the distally located TLK2 gene and SCYA chemokine gene cluster. The observation that the 17q breakpoint region could not be detected in any of the screened yeast artificial chromosome libraries and the localization of the 17q breakpoint in the vicinity of the distal breakpoints of two microdeletions in patients with neurofibromatosis type 1 suggest that this chromosomal region is genetically unstable and prone to rearrangements

Cadherins are major cell-cell adhesion proteins whose cytoplasmic domains bind to catenin proteins. Strong intercellular adhesion depends on linkage of the cadherin/catenin complex to the actin cytoskeleton via alpha -catenin. To date, it is not clear how different cell types achieve the variable strength of cell-cell adhesion clearly needed in a multicellular organism. Here, we report the cloning and molecular characterization of alphaE(testis)catenin, a novel human cDNA encoding a protein with homology to both human alphaE(epithelial)-catenin and alphaN(neural)-catenin. Although originally discovered in testis, alphaT-catenin is expressed in other tissues, the highest levels being observed in heart. Immunohistochemical analysis showed human alphaT-catenin localization at intercalated discs of cardiomyocytes and in peritubular myoid cells of testis. In cells transfected with alphaT-catenin cDNA, interaction with beta -catenin was demonstrated by coimmunoprecipitation. Transfection of alpha -catenin-deficient colon carcinoma cells recruited E-cadherin and beta -catenin to cell-cell contacts and functional cadherin-mediated cell-cell adhesion was restored in this way. Moreover, compaction of these cells was at least as prominent as in the case of cells expressing endogenous alphaE-catenin. We propose that alphaT-catenin is necessary for the formation of stretch-resistant cell-cell adhesion complexes, in particular, muscle cells.

Modeling the specificity of transcription factors to the DNA is one of the challenges that has kept many bioinformatics researchers busy since the early beginnings. Initially it was expected that a universal recognition code describing the amino acid to base pair contacts would be able to describe protein-DNA complex formation. However, until this very day a universal recognition code has not yet been found and alternative methods became more important. Nowadays, methods that describe the specificity of only one transcription factor (or a small family of transcription factors) are used most often. These methods make use of a set of experimentally validated binding sites to construct a profile for each transcription factor. One of the oldest profile-based methods is the consensus sequence method. Consensus sequences consist of a simple text string in which each character of the string represents the most prevalent nucleotide in the corresponding position of DNA binding sites. As an extension to these consensus sequences, in 1982, Gary Stormo introduced the well-known and very popular positional weight matrix (PWM). These PWMs consist of a 4xL matrix, with L being the length of the binding sites. In each row of these matrices, the frequency of occurrence of one of the four nucleotides is given for a certain position in the binding sites. Even though these PWMs are a big improvement to the consensus sequences method, they also lead to many false positive predictions. Many alternative methods try to improve the accuracy of these PWMs, most of them with very limited success. In this thesis I will discuss the shortcomings of the previous generation of prediction methods and I will suggest new methods that overcome some of these shortcomings. The first method that will be discussed in this thesis makes use of a multiple sequence alignment (MSA) to visualize evolutionary conserved transcription factor binding sites that are predicted with the PWM method. Binding sites that are conserved across all species in these alignments have a higher likelihood to be functional. Mutation of these binding sites would result in a less fit species, therefore mutations in these binding sites would have a negative effect. By inspecting these multiple sequence alignments for putative PWM hits we can reduce a large number of false positive predictions as false positive hits are less likely to be conserved. A second contribution of this thesis to the improvement of prediction methods is the research on and development of a number of new methods that make use of the structure and the biophysical characteristics of protein-DNA complexes. These characteristics are often overlooked in the previous generation of prediction methods even though they are very important for binding specificity in many protein-DNA complexes. With the help of the Random Forest classification method and sequence-based structural and biophysical characteristics we managed to develop models that can predict transcription factor binding sites with a higher level of accuracy. Based on this method, we also developed a user-friendly web-tool that can make use of a large number of pre-calculated transcription factor models.