High fertigation frequency and phosphorus level: Effects on summer-grown bell pepper growth and blossom-end rot incidence

The objective was to examine the effects of fertigation frequency and P application rate on bell pepper growth and blossom-end rot (BER) incidence, under hot conditions. The experiment comprised six treatments: two concentrations of phosphorus (3 and 30 mg L^–1) combined with three fertigation frequencies (two and eight events per day, and for 1.5 min every 25 min throughout the day). Increasing the fertigation frequency significantly increased the plants acquisition of nutrients, especially phosphorus and manganese. A significant linear regression was obtained between aboveground biomass, and leaf P concentration in the early vegetative stage. Based on the linear regression, 96% of the dry weight variations could be explained by differences in leaf P concentration, indicating that the main effect of fertigation frequency was related to improved P mobilization and uptake. Increasing the daily fertigation frequency from two to eight and to 30 applications reduced the number of BER fruits from 7 to 3 and to 2 per plant, respectively, and accordingly, increased the yield of export-quality fruits from 6.5 to 10 and to 10.5 per plant, respectively. The Mn concentration in plants exposed to low fertigation frequency were low, probably in the deficiency range, but they increased with increasing fertigation frequency. A negative correlation was found between the accumulated number of BER-affected fruits throughout the experiment and fruit-Mn concentrations. In light of recent findings that BER effects in the fruit tissue include the production of oxygen free-radicals and diminution of anti-oxidative compounds and enzymatic activities, and the known crucial role of manganese in enzyme activities and in detoxification of oxygen free-radicals, the relationships between BER incidence and fruit-Mn concentration may indicate that BER is related to Mn deficiency. Future researches are needed to validate this hypothesis.     

Nucleotide excision by E. coli DNA polymerase I in proofreading and non-proofreading modes

Escherichia coli DNA polymerase I exists in at least two distinct kinetic forms. When it binds to a template, the proofreading activity is usually switched off. As the enzyme progresses along the template, it becomes more and more competent for excision. This phenomenon introduces a link between fidelity and processivity. Processivity is best studied when the chain-length distributions of synthesized polymers are stationary. Even then, however, one cannot avoid multiple initiations on a given template by the same molecule of the enzyme. When synthesis is initiated with primers of lengths 15 or 20, a strange phenomenon is observed. It seems that the polymerase starts by hydrolyzing the primer down to a length of 7-10 nucleotides and only then starts to add nucleotides. It does so in a low-accuracy mode, suggesting that, while the exonuclease is clearly active, it does not contribute to proofreading. The warm-up of the proofreading function is therefore reinterpreted as a switch between two modes of behaviour: a mode 1 of low accuracy in which the 3'----5' exonuclease, while active, is uncoupled from the polymerase and does not contribute to proofreading, and a mode 2 of high accuracy in which the exonuclease is kinetically linked to the polymerase activity.     

Antifungal activities of essential oils applied by dip-treatment on areca palm (Areca catechu) leaf sheath and persistence of their potency upon storage

The antifungal activities of cinnamon oil, clove oil, anise oil, and peppermint oil, and their main components (cinnamaldehyde, eugenol, trans-anethole, and menthol, respectively) against molds identified from areca palm leaf sheath (Mucor dimorphosporus, Penicillium sp., Aspergillus niger, and Rhizopus sp.) were investigated. An agar dilution method was employed to determine the minimum inhibitory concentration (MIC) of essential oils and their main components. Zone inhibition tests and the inhibitory effect of the leaf sheath dip-treated with essential oils against those molds were examined. Major components of essential oils on the leaf sheath during storage were quantified by gas chromatography analysis. The MIC values of essential oils on agar and on the leaf sheath were identical. With an MIC of 50 ??g ml⁻¹, cinnamon oil had the strongest inhibitory effect. At their MICs the oils were capable of providing protection against mold growth on the leaf sheath for at least 12 weeks during storage at 25 °C and 100% RH. Scanning electron microscope examination showed that essential oils prevented spore germination. Except for menthol in peppermint oil, the main components of the essential oils, which were fairly stable over the storage period, largely contributed to the antifungal activity.     

Modification of LDL with human secretory phospholipase A(2) or sphingomyelinase promotes its arachidonic acid-releasing propensity

Oxidation and lipolytic remodeling of LDL are believed to stimulate LDL entrapment in the arterial wall, expanding the inflammatory response and promoting atherosclerosis. However, the cellular responses and molecular mechanisms underlying the atherogenic effects of lipolytically modified LDL are incompletely understood. Human THP-1 monocytes were prelabeled with [(3)H]arachidonic acid (AA) before incubation with LDL or LDL lipolytically modified by secretory PLA(2) (sPLA(2)) or bacterial sphingomyelinase (SMase). LDL elicited rapid and dose-dependent extracellular release of AA in monocytes. Interestingly, LDL modified by sPLA(2) or SMase displayed a marked increase in AA mobilization relative to native LDL, and this increase correlated with enhanced activity of cytosolic PLA(2) (cPLA(2)) assayed in vitro as well as increased monocyte tumor necrosis factor-alpha secretion. The AA liberation was attenuated by inhibitors toward cPLA(2) and sPLA(2), indicating that both PLA(2) enzymes participate in LDL-induced AA release. In conclusion, these results demonstrate that LDL lipolytically modified by sPLA(2) or SMase potentiates cellular AA release and cPLA(2) activation in human monocytes. From our results, we suggest novel atherogenic properties for LDL modified by sPLA(2) and SMase in AA release and signaling, which could contribute to the inflammatory gene expression observed in atherosclerosis.     

Biosynthesis of paf-acether. IX. Role for a phosphorylation-dependent activation of acetyltransferase in antigen-stimulated mouse mast cells

Mouse bone marrow-derived mast cells passively sensitized with monoclonal IgE released paf-acether (platelet-activating factor) and beta-hexosaminidase when challenged with the specific antigen. The formation and the release of paf-acether followed an early increase in the activity of the acetyltransferase, the main enzyme in paf-acether biosynthesis. The antigen-induced activation of the acetyltransferase was dependent on physiologic temperature and on the presence of Ca2+. By using microsomal fractions from unchallenged and challenged mast cells, the Vmax values were 3.5 and 12.0 nmol/min/mg of protein, respectively, whereas in both cases a Km value for acetyl-coenzyme A of 172 microM was measured. The stimulation of acetyltransferase could be mimicked in vitro under experimental conditions which favor phosphorylation, i.e. adding ATP and Mg2+ to lysates from unchallenged mast cells. In contrast, ATP and Mg2+ were uneffective on lysates from challenged cells that exhibited high level of acetyltransferase activity, suggesting that phosphorylation of the enzyme already took place at the time of cell stimulation. Moreover, addition of alkaline phosphatase to microsomal fraction obtained from either antigen-challenged mouse bone marrow-derived mast cells or unchallenged cells, resulted in 52% and 43% loss of acetyltransferase activity, respectively. Phorbol myristate acetate treatment of cells doubled the enzyme activity supporting the phosphorylation hypothesis. Thus, we report on the immunologic activation of a key enzyme for paf-acether synthesis and on the mechanism of this activation in a pure mast cell population. A link between bridging of IgE receptors and the activation of an enzyme critical to the formation of a lipid mediator is thereby evidenced.     

Functional analysis of novel multidrug transporters from human pathogens

Proteins of the Smr family are the smallest multidrug transporters, about 110 amino acids long, that extrude various drugs in exchange with protons, thereby rendering bacteria resistant to these compounds. One of these proteins, EmrE, is an Escherichia coli protein, which has been cloned based on its ability to confer resistance to ethidium and methyl viologen and which has been extensively characterized. More than 60 genes coding for Smr proteins have been identified in several bacteria based on amino acid sequence similarity to the emrE gene. In this work we have analyzed the sequence similarity among these homologues and identified some distinct signature sequence elements and several fully conserved residues. Five of these homologues, from human pathogens Mycobacterium tuberculosis, Bordetella pertussis, and Pseudomonas aeruginosa and from Escherichia coli, were cloned into an E. coli expression system. The proteins were further characterized and show varying degrees of methyl viologen uptake into proteoliposomes and [(3)H]TPP binding in solubilized membranes. The homologues can also form mixed oligomers with EmrE that exhibit intermediate binding characteristics. A comparative study of various homologous proteins provides a tool for deciphering structure-function relationship and monomer-monomer interaction in multidrug transporters and in membrane proteins in general.     

A structural EM algorithm for phylogenetic inference.

A central task in the study of molecular evolution is the reconstruction of a phylogenetic tree from sequences of current-day taxa. The most established approach to tree reconstruction is maximum likelihood (ML) analysis. Unfortunately, searching for the maximum likelihood phylogenetic tree is computationally prohibitive for large data sets. In this paper, we describe a new algorithm that uses Structural Expectation Maximization (EM) for learning maximum likelihood phylogenetic trees. This algorithm is similar to the standard EM method for edge-length estimation, except that during iterations of the Structural EM algorithm the topology is improved as well as the edge length. Our algorithm performs iterations of two steps. In the E-step, we use the current tree topology and edge lengths to compute expected sufficient statistics, which summarize the data. In the M-Step, we search for a topology that maximizes the likelihood with respect to these expected sufficient statistics. We show that searching for better topologies inside the M-step can be done efficiently, as opposed to standard methods for topology search. We prove that each iteration of this procedure increases the likelihood of the topology, and thus the procedure must converge. This convergence point, however, can be a suboptimal one. To escape from such "local optima," we further enhance our basic EM procedure by incorporating moves in the flavor of simulated annealing. We evaluate these new algorithms on both synthetic and real sequence data and show that for protein sequences even our basic algorithm finds more plausible trees than existing methods for searching maximum likelihood phylogenies. Furthermore, our algorithms are dramatically faster than such methods, enabling, for the first time, phylogenetic analysis of large protein data sets in the maximum likelihood framework.     

Errors and alternatives in prebiotic replication and catalysis

The work on nonenzymatic nucleic acid replication performed by Leslie Orgel and co-workers over the last four decades, now extended by work on artificial selection of RNA aptamers and ribozymes, is generating some pessimism concerning the 'naked gene' theories of the origin of life. It is suggested here that the low probability of finding RNA aptamers and ribozymes within pools of random sequences is not as disquieting as the poor gain in efficiency obtained with increases in information content. As acknowledged by Orgel and many other authors, primitive RNA replication and catalysis must have occurred within already complex and dynamic environments. I, thus, propose to pay attention to a number of possibilities that bridge the gap between 'naked gene' theories, on one side, and metabolic theories in which complex systems self-propagate by growth and fragmentation, on the other side. For instance, one can de-emphasize nucleotide-by-nucleotide replication leading to long informational polymers, and view instead long random polymers as storage devices, from which shorter oligomers are excised. Catalytic tasks would be mainly performed by complexes associating two or more oligomers belonging to the same or to different chemical families. It is proposed that the problems of stability, binding affinity, reactivity, and specificity could be easier to handle by heterogeneous complexes of short oligomers than by long, single-stranded polymers. Finally, I point out that replication errors in a primitive replication context should include incorporations of alternative nucleotides with interesting, chemically reactive groups. In this way, an RNA sequence could be at the same time an inert sequence when copied without error, and a ribozyme, when a chemically reactive nucleotide is inadvertently introduced during replication.     

Phylogeny reconstruction: increasing the accuracy of pairwise distance estimation using Bayesian inference of evolutionary rates

Distance-based methods for phylogeny reconstruction are the fastest and easiest to use, and their popularity is accordingly high. They are also the only known methods that can cope with huge datasets of thousands of sequences. These methods rely on evolutionary distance estimation and are sensitive to errors in such estimations. In this study, a novel Bayesian method for estimation of evolutionary distances is developed. The proposed method enables the use of a sophisticated evolutionary model that better accounts for among-site rate variation (ASRV), thereby improving the accuracy of distance estimation. Rate variations are estimated within a Bayesian framework by extracting information from the entire dataset of sequences, unlike standard methods that can only use one pair of sequences at a time. We compare the accuracy of a cascade of distance estimation methods, starting from commonly used methods and moving towards the more sophisticated novel method. Simulation studies show significant improvements in the accuracy of distance estimation by the novel method over the commonly used ones. We demonstrate the effect of the improved accuracy on tree reconstruction using both real and simulated protein sequence alignments. An implementation of this method is available as part of the SEMPHY package.