Tenascin-C Enhances Pancreatic Cancer Cell Growth and Motility and Affects Cell Adhesion through Activation of the Integrin Pathway

Background: Pancreatic cancer (PDAC) is characterized by an abundant fibrous tissue rich in Tenascin-C (TNC), a large ECM glycoprotein mainly synthesized by pancreatic stellate cells (PSCs). In human pancreatic tissues, TNC expression increases in the progression from low-grade precursor lesions to invasive cancer. Aim of this study was the functional characterization of the effects of TNC on biologic relevant properties of pancreatic cancer cells. Methods: Proliferation, migration and adhesion assays were performed on pancreatic cancer cell lines treated with TNC or grown on a TNC-rich matrix. Stable transfectants expressing the large TNC splice variant were generated to test the effects of endogenous TNC. TNC-dependent integrin signaling was investigated by immunoblotting, immunofluorescence and pharmacological inhibition. Results: Endogenous TNC promoted pancreatic cancer cell growth and migration. A TNC-rich matrix also enhanced migration as well as the adhesion to the uncoated growth surface of poorly differentiated cell lines. In contrast, adhesion to fibronectin was significantly decreased in the presence of TNC. The effects of TNC on cell adhesion were paralleled by changes in the activation state of paxillin and Akt. Conclusion: TNC affects proliferation, migration and adhesion of poorly differentiated pancreatic cancer cell lines and migh

The European Reference Genome Atlas: piloting a decentralised approach to equitable biodiversity genomics.

ABSTRACT: A global genome database of all of Earth’s species diversity could be a treasure trove of scientific discoveries. However, regardless of the major advances in genome sequencing technologies, only a tiny fraction of species have genomic information available. To contribute to a more complete planetary genomic database, scientists and institutions across the world have united under the Earth BioGenome Project (EBP), which plans to sequence and assemble high-quality reference genomes for all ∼1.5 million recognized eukaryotic species through a stepwise phased approach. As the initiative transitions into Phase II, where 150,000 species are to be sequenced in just four years, worldwide participation in the project will be fundamental to success. As the European node of the EBP, the European Reference Genome Atlas (ERGA) seeks to implement a new decentralised, accessible, equitable and inclusive model for producing high-quality reference genomes, which will inform EBP as it scales. To embark on this mission, ERGA launched a Pilot Project to establish a network across Europe to develop and test the first infrastructure of its kind for the coordinated and distributed reference genome production on 98 European eukaryotic species from sample providers across 33 European countries. Here we outline the process and challenges faced during the development of a pilot infrastructure for the production of reference genome resources, and explore the effectiveness of this approach in terms of high-quality reference genome production, considering also equity and inclusion. The outcomes and lessons learned during this pilot provide a solid foundation for ERGA while offering key learnings to other transnational and national genomic resource projects.info:eu-repo/semantics/publishedVersio

25th annual computational neuroscience meeting: CNS-2016

The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong

Deep learning study of tyrosine reveals that roaming can lead to photodamage

Amino acids are among the building blocks of life, forming peptides and proteins, and have been carefully ‘selected’ to prevent harmful reactions caused by light. To prevent photodamage, molecules relax from electronic excited states to the ground state faster than the harmful reactions can occur; however, such photochemistry is not fully understood, in part because theoretical simulations of such systems are extremely expensive—with only smaller chromophores accessible. Here, we study the excited-state dynamics of tyrosine using a method based on deep neural networks that leverages the physics underlying quantum chemical data and combines different levels of theory. We reveal unconventional and dynamically controlled ‘roaming’ dynamics in excited tyrosine that are beyond chemical intuition and compete with other ultrafast deactivation mechanisms. Our findings suggest that the roaming atoms are radicals that can lead to photodamage, offering a new perspective on the photostability and photodamage of biological systems

Workshop "Frontiers in Cultural Studies"

International audienc

Effects of endogenous TNC on cell proliferation and migration.

<p>PANC-1 cells were stably transfected with a vector driving the expression of <i>large</i> TNC (PANC-T2, PANC-T24 and PANC-T27 cells) and with the empty vector (PANC-C21, PANC-C23 and PANC-C27 cells). (A) Immunoblotting of precipitated cell culture medium of the transfected PANC-1 cells grown up to 80% confluence. To ensure that a comparable number of transfected cells was the source of secreted TNC, GAPDH expression in whole cell extracts was tested. PANC-T2 cells show the highest levels of secreted TNC, while lower levels are observed in PANC-T24 and PANC-T27. The control clones in comparison do not show any TNC secretion. (B) Cells were grown in complete medium. Growth was determined with MTT assay at different time points (24, 48 and 72 hours). Data are calculated as mean +/− s.e.m. of three experiments and are expressed as percentage compared to the PANC-1 cells (°p<0.05, *p<0.01, **p<0.001, Students two-tailed t test). The proliferation rate is significantly higher for PANC-T2 at all time points (p<0.001), for PANC-T24 at 24 hours (p<0.001) and at 48 hours (p = 0.022) and for PANC-T27 at 24 (p<0.001) and 48 hours (p = 0.009). (C) The proliferation of all the PANC-1 positive clones (PT) compared to the mock transfected cells (PC) is significantly higher for each tested time point (24 hours: p = 0.004, 48 hours: p = 0.012, 72 hours: p = 0.026) (D) Transfected PANC-1 cells were plated, after 24 hours medium was changed with medium containing 0.1% FBS and, after overnight incubation, the monolayer was scraped with a 10 µl pipette tip. Data are calculated as described in B. In comparison to the non transfected PANC-1 cells, migration is significantly faster for PANC-T2 (p<0.001 at both time points) and for PANC-T27 (p = 0.042 at 24 hours; p = 0.009 at 48 hours). (E) All together, the PANC-1 positive clones (PT) migrate significantly faster compared to the mock transfected cells (PC) at both time points (p<0.001).</p

Effects of exogenous TNC on pancreatic cancer cell growth.

<p>(A) Cells were grown for 72 hours in serum free medium containing different concentrations of TNC (0.01, 0.1, 1 and 10 µg/ml). (B) Cells were grown for 72 hours in serum free medium onto TNC coated plates (1 µg/cm²). Growth was determined with MTT assay. Data are calculated as mean +/− s.e.m. of three experiments and are expressed as percentage compared to the untreated controls (°p<0.05, *p<0.01, **p<0.001, Students two-tailed t test).</p

Cellular distribution of phospho-paxillin and vinculin proteins on coated surfaces.

<p>PANC-1 cells were let adhere to uncoated or TNC, FN and FN/TNC coated coverslips for 45 min, gently washed, fixed and stained using fluorescent secondary antibodies. Focal adhesion plaques were evidenced by co-localization of vinculin (green) and phospho-paxillin (pPAX, red). Cell nuclei were counterstained with Hoechst 33342.</p

Effect of TNC on the migration of pancreatic cancer cell lines.

<p>(A)Cells were plated onto uncoated plates and after 24 hours the monolayer was scraped with a 10 µl pipette tip. Cells were then incubated in serum free medium or in medium with the addition of TNC at different concentrations (0.2 µg/ml, 1 µg/ml and 5 µg/ml) up to 48 hours. (B) Cells were plated onto 24-well plates coated with three different concentrations of TNC (0.1 µg/cm², 0.5 µg/cm² and 2.5 µg/cm²) or onto uncoated plates and after 24 hours the monolayer was scraped with a 10 µl pipette tip. Cells were then incubated in serum free medium up to 48 hours. Migration of cells into wounded areas was evaluated counting migrated cells manually and by the TScratch software <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0021684#pone.0021684-Geback1" target="_blank">[36]</a> and a total of 2–8 fields were counted per group in each experiment. Data are calculated as mean +/− s.e.m. and expressed as fold-change compared to the non treated cells (°p<0.05, *p<0.01, **p<0.001, Students two-tailed t test).</p