Action of phorbol esters in cell culture: Mimicry of transformation,altered differentiation,and effects on cell membranes

The carcinogenic process is usually multifactor in its causation and multistep in its evolution. It is likely that entirely different molecular mechanisms underlie the many steps in this process. In contrast t o initiating carcinogens, the action of the tumor-promoting phorbol esters does not appear t o involve covalent binding t o cellular DNA and they are not mutagenic. Recent studies in cell culture have revealed two interesting biologic effects of the phorbol esters and related macrocyclic plant diterpenes. The first is that at nanomolar concentrations they induce several changes that resemble those seen in cells transformed by chemical carcinogens or tumor viruses. These include altered morphology and increased saturation density, altered cell surface fucose-glycopeptides, decrease in the LETS protein, increased transport of deoxyglucose, and increased levels of plasminogen activator and ornithine decarboxylase. In transformed cells exposed to phorbol esters the expression of these features is further accentuated. Phorbol esters do not induce normal cells to grow in agar but they do enhance the growth in agar of certain transformed cells. The second effect of the phorbol esters is inhibition of terminal differentiation. This effect extends to a variety of programs of differentiation and is reversible when the agent is removed. With certain cell culture systems induction of differentiation, rather than inhibition, is observed. Both the transformation mimetic and the differentiation effects are exerted by plant diterpenes that have tumor-promoting activity but not by congeners that lack such activity. The primary target of phorbol esters appears to be the cell membrane. Early membrane-related effects include enhanced uptake of 2-deoxyglucose and other nutrients, altered cell adhesion, induction of arachidonic acid release and prostaglandin synthesis, inhibition of the binding of epidermal growth factor t o cell surface receptors, altered lipid metabolism, and modifications in the activities of other cell surface receptors. A model of “two stage” carcinogenesis encompassing the known molecular and cellular effects of initiating carcinogens and tumor promoters is presented. According to this model, initiating carcinogens induce stable alterations in the cellular genome but these are not manifested until tumor promoters modulate programs of gene expression and induce the clonal outgrowth of the initiated cell.     

Hydrogen Peroxide Formation by Cells Treated with a Tumor Promoter

To determine whether oxidants capable of DNA modification are produced by cells treated with tumor promoters, we adapted a fluorometric method to our needs. HeLa cells were preincubated with 2‘,7‘-dichlorofluorescin diacetate (DCFdAc), treated with various agents, sonicated. centrifuged and fluorescence of the oxidized product (DCF) was determined in supernatants. When cells were exposed to H₂O₂ in the presence of azide (catalase inhibitor) or o-phenanthroline (a lipophilic Fe chelator), an increase in fluorescence was observed. These results show that some Fe ions were interacting with the H₂O₂ which entered the cells, thus decreasing its levels available for oxidation of the substrate and potentially increasing formation of OH, known DNA-damaging species. Glutathione (GSH). which is present in cells in substantial amounts, was found to reduce DCF whereas azide counteracted GSH-mediated reduction.

Treatment of HeLa cells with 12–0-tetradecanoyl-phorbol-13-acetate (TPA) in the presence of DCFdAc and azide resulted in dose-and time-dependent formation of DCF. Even when cells were sonicated prior to incubation with TPA, DCF was formed at levels proportional to the number of cells as well as dose of TPA. Flow cytometry of TPA-treated cells confirmed these findings.

These results demonstrate that tumor promoters can cause oxidative activation of HeLa cells, which produce active oxygen species, most likely H₂O₂, that ultimately contribute to the formation of oxidized bases such as 5-hydroxymethyl uracil in cellular DNA. They also show that this fluorometric method can be utilized for determination of cellular H₂O₂ formation at nM concentrations.     

Modulating the structure of phenylalanine‐incorporated ascidiacyclamide through fluorination

We designed four fluorinated Phe‐incorporated ascidiacyclamide ([Phe]ASC) analogs, (cyclo(?Xxx1‐oxazoline2‐d ‐Val3‐thiazole4‐Ile5‐oxazoline6‐d ‐Val7‐thiazole8‐)), [(4‐F)Phe]ASC (Xxx1: 4‐fluorophenylalanine), [(3,5‐F₂)Phe]ASC (Xxx1: 3,5‐difluorophenylalanine), [(3,4,5‐F₃)Phe]ASC (Xxx1: 3,4,5‐trifluorophenylalanine) and [(F₅)Phe]ASC (Xxx1: pentafluorophenylalanine), to modulate the π‐electron density of the aromatic ring of the Phe residue. X‐ray diffraction analysis, ¹H NMR and CD spectra all suggested that the interactions between the benzene ring of the Xxx1 residue and the alkyl groups of oxazoline2 contribute to the stability of the folded structure of these analogs. Substituting fluorines for the hydrogens progressively weakened those interactions through reducing the π‐electron density, thereby mediating transformation from the folded to square structure. As a result, [(F₅)Phe]ASC preferred the square form more than the other analogs did. Also contributing to the preference for the square form may be the hindrance of the rotation around the Cα–Cβ bond by the two ortho‐fluoro substituents of [(F₅)Phe]ASC. These findings demonstrate that the structure of ASC can be modulated by using fluorine as an electron‐withdrawing group. Copyright © 2014 European Peptide Society and John Wiley & Sons, Ltd.     

Cloning of new rubisco promoters from <Emphasis Type="Italic">Brassica rapa</Emphasis> and determination of their activity in stably transformed <Emphasis Type="Italic">Brassica napus</Emphasis> and <Emphasis Type="Italic">Nicotiana tabacum</Emphasis> plants

The aim of our study was to identify the highest expressing rubisco small subunit (RbcS) promoters (pRbcS) from the cotyledons of germinating seedlings of Brassica rapa var. oleifera to drive high-level and preferably stage-specific transgenic protein expression in Brassicaceae plants. We cloned four new pRbcS promoters using several approaches, including the construction of a cDNA library and use of genome walking technique. Real-time PCR analysis of RbcS mRNA expression clearly showed that two of these promoters exhibited the highest activity on the germination stage of plant development. We used gusA expression as a reporter of promoter activity in Brassica napus and Nicotiana tabacum plants that were transformed with the constructs using an Agrobacterium-mediated transformation strategy. The mRNA level of RbcS and of gusA was quantified in transformed plants. The data obtained demonstrate that the promoter most active in seedlings under native conditions was also most active in transgenic constructs at the same stage of plant development. The fine structure of the promoters is discussed herein.     

Localization of neural efficiency of the mathematically gifted brain through a feature subset selection method

Based on the neural efficiency hypothesis and task-induced EEG gamma-band response (GBR), this study investigated the brain regions where neural resource could be most efficiently recruited by the math-gifted adolescents in response to varying cognitive demands. In this experiment, various GBR-based mental states were generated with three factors (level of mathematical ability, task complexity, and short-term learning) modulating the level of neural activation. A feature subset selection method based on the sequential forward floating search algorithm was used to identify an “optimal” combination of EEG channel locations, where the corresponding GBR feature subset could obtain the highest accuracy in discriminating pairwise mental states influenced by each experiment factor. The integrative results from multi-factor selections suggest that the right-lateral fronto–parietal system is highly involved in neural efficiency of the math-gifted brain, primarily including the bilateral superior frontal, right inferior frontal, right-lateral central and right temporal regions. By means of the localization method based on single-trial classification of mental states, new GBR features and EEG channel-based brain regions related to mathematical giftedness were identified, which could be useful for the brain function improvement of children/adolescents in mathematical learning through brain–computer interface systems.     

Comprehensive construction strategy of bidirectional green tissue‐specific synthetic promoters

Bidirectional green tissue‐specific promoters have important application prospects in genetic engineering and crop genetic improvement. However, there is no report on the application of them, mainly due to undiscovered natural bidirectional green tissue‐specific promoters and the lack of a comprehensive approach for the synthesis of these promoters. In order to compensate for this vacancy, the present study reports a novel strategy for the expression regulatory sequence selection and the bidirectional green tissue‐specific synthetic promoter construction. Based on this strategy, seven promoters were synthesized and introduced into rice by agrobacterium‐mediated transformation. The functional identification of these synthetic promoters was performed by the expression pattern of GFP and GUS reporter genes in two reverse directions in transgenic rice. The results indicated that all the synthetic promoters possessed bidirectional expression activities in transgenic rice, and four synthetic promoters (BiGSSP2, BiGSSP3, BiGSSP6, BiGSSP7) showed highly bidirectional expression efficiencies specifically in green tissues (leaf, sheath, panicle, stem), which could be widely applied to agricultural biotechnology. Our study provided a feasible strategy for the construction of synthetic promoters, and we successfully created four bidirectional green tissue‐specific synthetic promoters. It is the first report on bidirectional green tissue‐specific promoters that could be efficiently applied in genetic engineering.     

Characterization of ecosystem responses to climatic controls using artificial neural networks

Understanding and modeling ecosystem responses to their climatic controls is one of the major challenges for predicting the effects of global change. Usually, the responses are implemented in models as parameterized functional relationships of a fixed type. In contrast, the inductive approach presented here based on artificial neural networks (ANNs) allows the relationships to be extracted directly from the data. It has been developed to explore large, fragmentary, noisy, and multidimensional datasets, such as the carbon fluxes measured at the ecosystem level with the eddy covariance technique. To illustrate this, our approach has been systematically applied to the daytime carbon flux dataset of the deciduous broadleaf forest Hainich in Germany. The total explainable variability of the half‐hourly carbon fluxes from the driving climatic variables was 93.1%, showing the excellent data mining capability of the ANNs. Total photosynthetic photon flux density was identified as the dominant control of the daytime response, followed by the diffuse radiation. The vapor pressure deficit was the most important nonradiative control. From the ANNs, we were also able to deduce and visualize the dependencies and sensitivities of the response to its climatic controls. With respect to diffuse radiation, the daytime carbon response showed no saturation and the light use efficiency was three times greater for diffuse compared with direct radiation. However, with less potential radiation reaching the forest, the overall effect of diffuse radiation was slightly negative. The optimum uptake of carbon occurred at diffuse fractions between 30% and 40%. By identifying the hierarchy of the climatic controls of the ecosystem response as well as their multidimensional functional relationships, our inductive approach offers a direct interface to the data. This provides instant insight in the underlying ecosystem physiology and links the observational relationships to their representation in the modeling world.