148 research outputs found
A novel expression cassette for the efficient visual selection of transformed tissues in florist's chrysanthemum (Chrysanthemum morifolium Ramat.)
Constructs carrying visual reporter genes coupled with efficient promoters could facilitate the process of identification and selection of stable transformants in recalcitrant crops. Here, a novel construct utilizing a ribulose-1,5-bisphosphate carboxylase (RbcS) promoter combined with the green fluorescent protein (GFP) reporter gene to initiate very high expression of GFP in florist's chrysanthemum (Chrysanthemum morifolium Ramat.) was described. Based on this expression cassette, a new regeneration protocol using leaf discs as explants was developed for the Agrobacterium-mediated transformation of Chrysanthemum genotype ‘1581’, and a transformation efficiency of 7% was obtained. The expression of two different GFP constructs targeted to either cytosol or plastids was compared in transgenic lines. Both GFP constructs were expressed at such a high level that the green fluorescence dominated red fluorescence in the leaf tissues, allowing easy observation and microdissection of transformed tissues even without a GFP filter. Under normal light, plants with GFP targeted to plastids had a light green phenotype deriving from the high GFP expression. Quantitative reverse transcriptional PCR analysis showed that the plastid targeted construct with intron had significantly higher steady state transcript levels of GFP mRNA. This novel expression cassette may allow direct visual selection of transformed tissues independent of antibiotic selection in a wide range of plant species.Key words: Florist's chrysanthemum (Chrysanthemum morifolium), genetic transformation, GFP gene, RbcS promoter, RbcS targeting signal
Kinetics of neuroendocrine differentiation in an androgen-dependent human prostate xenograft model
Kinetics of neuroendocrine differentiation in an androgen-dependent human prostate xenograft model
Responsible innovation in stem cell research: using responsibility as a strategy
Responsible innovation has been introduced as an important condition for advancing the field of regenerative medicine. This is reflected in the frequent references to responsible research conduct and responsible innovation in guidelines and recommendations in academic literature. The meaning of responsibility, how responsibility could be fostered and the context in which responsibilities should be enacted, however, remain unclear. The goal of this paper is to clarify the concept of responsibility in stem cell research and to illustrate how this concept could inform strategies to deal effectively with the ethical implications of stem cell research. Responsibility can be dissected into four categories: responsibility-As-Accountability, responsibility-As-liability, responsibility-As-An-obligation and responsibility-As-A-virtue. The authors focus on responsible research conduct and responsible innovation in general to move beyond the scope of research integrity and illustrate that different notions of responsibility have different implications for how stem cell research is organized. Plain language summary Literature and guidelines mention that responsible innovation could help the field of stem cell research to deal with ethical challenges. However, in this literature and guidelines it does not become clear how a'responsibility' should be understood, how responsibilities are recognized, how responsibilities are shared and how someone could take responsibility. In this article, different types of responsibility are discussed: responsibility-As-Accountability, responsibility-As-liability, responsibility-As-An-obligation and responsibility-As-A-virtue. The types are discussed according to how they are different from one another and how they can be used to organize stem cell research. It is shown that these different types of responsibility help not only with research integrity issues but also with societal and other types of ethical challenges. Tweetable abstract Responsible innovation could advance the field of stem cell research. By considering different notions of responsibility, possibilities emerge to frame ethical challenges and organize stem cell research accordingly. #ResponsibleInnovation #StemCells #Bioethic
Development and Validation of Predictive Model for a Diagnosis of First Episode Psychosis Using the Multinational EU-GEI Case–control Study and Modern Statistical Learning Methods
Background and Hypothesis: It is argued that availability of diagnostic models will facilitate a more rapid identification of individuals who are at a higher risk of first episode psychosis (FEP). Therefore, we developed, evaluated, and validated a diagnostic risk estimation model to classify individual with FEP and controls across six countries. /
Study Design: We used data from a large multi-center study encompassing 2627 phenotypically well-defined participants (aged 18-64 years) recruited from six countries spanning 17 research sites, as part of the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions study. To build the diagnostic model and identify which of important factors for estimating an individual risk of FEP, we applied a binary logistic model with regularization by the least absolute shrinkage and selection operator. The model was validated employing the internal-external cross-validation approach. The model performance was assessed with the area under the receiver operating characteristic curve (AUROC), calibration, sensitivity, and specificity. /
Study Results: Having included preselected 22 predictor variables, the model was able to discriminate adults with FEP and controls with high accuracy across all six countries (rangesAUROC=0.84-0.86). Specificity (range=73.9-78.0%) and sensitivity (range=75.6-79.3%) were equally good, cumulatively indicating an excellent model accuracy; though, calibration slope for the diagnostic model showed a presence of some overfitting when applied specifically to participants from France, the UK, and The Netherlands. /
Conclusions: The new FEP model achieved a good discrimination and good calibration across six countries with different ethnic contributions supporting its robustness and good generalizability
Selective Loss of Cysteine Residues and Disulphide Bonds in a Potato Proteinase Inhibitor II Family
Disulphide bonds between cysteine residues in proteins play a key role in protein folding, stability, and function. Loss of a disulphide bond is often associated with functional differentiation of the protein. The evolution of disulphide bonds is still actively debated; analysis of naturally occurring variants can promote understanding of the protein evolutionary process. One of the disulphide bond-containing protein families is the potato proteinase inhibitor II (PI-II, or Pin2, for short) superfamily, which is found in most solanaceous plants and participates in plant development, stress response, and defence. Each PI-II domain contains eight cysteine residues (8C), and two similar PI-II domains form a functional protein that has eight disulphide bonds and two non-identical reaction centres. It is still unclear which patterns and processes affect cysteine residue loss in PI-II. Through cDNA sequencing and data mining, we found six natural variants missing cysteine residues involved in one or two disulphide bonds at the first reaction centre. We named these variants Pi7C and Pi6C for the proteins missing one or two pairs of cysteine residues, respectively. This PI-II-7C/6C family was found exclusively in potato. The missing cysteine residues were in bonding pairs but distant from one another at the nucleotide/protein sequence level. The non-synonymous/synonymous substitution (Ka/Ks) ratio analysis suggested a positive evolutionary gene selection for Pi6C and various Pi7C. The selective deletion of the first reaction centre cysteine residues that are structure-level-paired but sequence-level-distant in PI-II illustrates the flexibility of PI-II domains and suggests the functionality of their transient gene versions during evolution
p53 modeling as a route to mesothelioma patients stratification and novel therapeutic identification
Background
Malignant pleural mesothelioma (MPM) is an orphan disease that is difficult to treat using traditional chemotherapy, an approach which has been effective in other types of cancer. Most chemotherapeutics cause DNA damage leading to cell death. Recent discoveries have highlighted a potential role for the p53 tumor suppressor in this disease. Given the pivotal role of p53 in the DNA damage response, here we investigated the predictive power of the p53 interactome model for MPM patients’ stratification.
Methods
We used bioinformatics approaches including omics type analysis of data from MPM cells and from MPM patients in order to predict which pathways are crucial for patients’ survival. Analysis of the PKT206 model of the p53 network was validated by microarrays from the Mero-14 MPM cell line and RNA-seq data from 71 MPM patients, whilst statistical analysis was used to identify the deregulated pathways and predict therapeutic schemes by linking the affected pathway with the patients’ clinical state.
Results
In silico simulations demonstrated successful predictions ranging from 52 to 85% depending on the drug, algorithm or sample used for validation. Clinical outcomes of individual patients stratified in three groups and simulation comparisons identified 30 genes that correlated with survival. In patients carrying wild-type p53 either treated or not treated with chemotherapy, FEN1 and MMP2 exhibited the highest inverse correlation, whereas in untreated patients bearing mutated p53, SIAH1 negatively correlated with survival. Numerous repositioned and experimental drugs targeting FEN1 and MMP2 were identified and selected drugs tested. Epinephrine and myricetin, which target FEN1, have shown cytotoxic effect on Mero-14 cells whereas marimastat and batimastat, which target MMP2 demonstrated a modest but significant inhibitory effect on MPM cell migration. Finally, 8 genes displayed correlation with disease stage, which may have diagnostic implications.
Conclusions
Clinical decisions related to MPM personalized therapy based on individual patients’ genetic profile and previous chemotherapeutic treatment could be reached using computational tools and the predictions reported in this study upon further testing in animal models
LPA Is a Chemorepellent for B16 Melanoma Cells: Action through the cAMP-Elevating LPA5 Receptor
Lysophosphatidic acid (LPA), a lipid mediator enriched in serum, stimulates cell migration, proliferation and other functions in many cell types. LPA acts on six known G protein-coupled receptors, termed LPA1–6, showing both overlapping and distinct signaling properties. Here we show that, unexpectedly, LPA and serum almost completely inhibit the transwell migration of B16 melanoma cells, with alkyl-LPA(18∶1) being 10-fold more potent than acyl-LPA(18∶1). The anti-migratory response to LPA is highly polarized and dependent on protein kinase A (PKA) but not Rho kinase activity; it is associated with a rapid increase in intracellular cAMP levels and PIP3 depletion from the plasma membrane. B16 cells express LPA2, LPA5 and LPA6 receptors. We show that LPA-induced chemorepulsion is mediated specifically by the alkyl-LPA-preferring LPA5 receptor (GPR92), which raises intracellular cAMP via a noncanonical pathway. Our results define LPA5 as an anti-migratory receptor and they implicate the cAMP-PKA pathway, along with reduced PIP3 signaling, as an effector of chemorepulsion in B16 melanoma cells
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