Spectroscopic studies of the manganese complex of Photosystem II

Our recent EPR and EXAFS experiments investigating the structure of the oxygen-evolving complex of PS II are discussed. PS II treatments which affect the cofactors calcium and chloride have been used to poise samples in modified forms of the S-states, S₁, S₂ and S₃. X-ray absorption studies indicate a similar overall structure for the manganese complex between treated and native samples although the influence of the treatments and cofactors is observed. Manganese oxidation (or oxidation of a ligand to the manganese cluster) is indicated to occur on each of the transitions S₁ S₂ and S₂ S₃ in these modified samples. The cluster appears to contain at least two inequivalent Mn-Mn pairs. In the native samples the Mn-Mn distance is 2.7 Å, but in samples where the calcium site is affected, one of the pairs has a 3.0 Å Mn-Mn distance. The intensity of the 3.3/3.6 Å interaction is reduced on sodium chloride treatment (calcium depletion) perhaps indicating calcium binding close to the manganese cluster. From EPR data we also propose that treatments which affect calcium and chloride binding cause a modification of the native S₂ state, slow the reduction of Y_z and allow an S3 EPR signal to be observed following illumination. The origin of the S3 EPR signal, a modified S₃ or S₂ X where X is an organic radical of unknown charge, is discussed in relation to the results from the EXAFS studies.Abbreviations EPR electron paramagnetic resonance spectroscopy - EXAFS extended X-ray absorption fine structure - HTG n-heptyl -d-thioglucoside - MES 2(N-morpholino)ethanesulfonic acid - OEC oxygen evolving complex - PPBQ phenyl-1,4-benzoquinone - PS II Photosystem II - Y_z redox active tyrosine     

A highly conserved α-tubulin sequence from Prunus amygdalus

The sequence of an -tubulin from Prunus amygdalus has been obtained by cDNA cloning. When this sequence is compared to that of the Tub1 gene from maize it shows a very high degree of similarity, much higher than any of the -tubulin sequences reported so far from plants. The expression of this gene is high in the stages of seed development where a high divisional activity is present. It is preferentially expressed in the radicular tissues as it is gene Tub1 in maize. Southern analysis indicates that this gene may from a subfamily of -tubulin genes having similar sequence and tissue specificity and existing at least in maize and in Prunus.     

Peroxisome proliferators as inducers and substrates of UDP-glucuronosyltransferases

Summary— Peroxisome proliferators, despite their chemically unrelated structures, share the common property of being able to stimulate the glucuronidation of bilirubin in rodents and, probably, also in man. The aryloxycarboxylic acids (clofibric acid, fenofibrate, bezafibrate, ciprofibrate), tiadenol and probucol, all of which have hypolipidemic properties, as well as the fatty acid-like perfluorodecanoic acid all enhanced the expression of the UDP-glucuronosyltransferase (UGT) form involved in the conjugation of the pigment. This induction is manifested by an increase in the mRNA species encoding the protein with a subsequent increase in the neosynthesis of the corresponding protein in the endoplasmic reticulum. The induction process is concomitant with that of cytochrome P-450-IVA1 and cytosolic epoxide hydrolase, which, like bilirubin UGT, are mainly involved in the metabolism of endogenous substrates. With a series of carboxylic acids related to clofibric acid, it was possible to demonstrate that induction was mediated via specific interactions based on the physicochemical properties of the inducers. Until now, the molecular basis of induction of bilirubin UGT is not known. The peroxisome proliferators that possess a carboxyl group are good substrates of UGT, especially in man. The acylglucuronides formed are known for their instability and reactivity which could contribute to the toxicity encountered in some patients treated with the drugs. There is convincing evidence that UGT bilirubin does not catalyze the glucuronidation of these substances even if the two types of substrate form acylglucuronides.     

Perspectives on environmental risk assessment

Risk is by no means a simple concept. Natural variability and definitional problems with the concept of probability complicate the measurement and use of risk as an analytical tool. Variability requires that risk assessment methods separate natural from total risk when attempting to estimate anthropogenic risk. Failure to do so results in the over estimation of anthropogenic risk and the eventual loss of credibility for risk assessment methodologies. The common frequentist approach to probability is not consistent with anything but a modelling approach to risk assessment. When combined with its ability to account for natural variability, incorporate laboratory-assay data and offer complete statistical and experimental control, modelling is a promising approach to risk assessment. Modelling, however, is not without its drawbacks. Initialization bias can result in the over, or under, estimation of both natural and anthropogenic risk. Furthermore, model estimates are time dependent. The convergence of natural and anthropogenic risk poses problems for modelling-based risk assessment and requires clear statements as to the importance of the time dimension in risk assessment. When combined, the drawbacks to modelling-based risk assessment argue that risk should never be stated as a scalar quantity. Instead, modelling-based risk assessment should provide estimates of the complete range of risk measures (total, natural, and anthropogenic) as well as indications of convergence time. Only then can the modelling-based approach be viewed as the most appropriate means of carrying out scientifically credible risk assessment.     

A Julia set model of field-directed morphogenesis: developmental biology and artificial life

One paradigm used in understanding the control of morpho-geneticevents is the concept of positional information, where sub-organismiccomponents (such as cells) act in response to positional cues.It is important to determine what kinds of spatiotemporal patternsmay be obtained by such a method, and what the characteristicsof such a morphogenetic process might be. This paper presentsa computer model of morphogenesis based on gene activity drivenby interpreting a positional information field. In this model,the interactions of mutually regulating developmental genesare viewed as a map from R² to R², and are modeled by the complexnumber algebra. Functions in complex variables are used to simulategenetic interactions resulting in position-dependent differentiation.This is shown to be equivalent to computing modified Julia sets,and is seen to be sufficient to produce a very rich set of morphologieswhich are similar in appearance and several important characteristicsto those of real organisms. The properties of this model canbe used to study the potential role of fields and positionalinformation as guiding factors in morphogenesis, as the modelfacilitates the study of static images, time-series (movies)and experimental alterations of the developmental process. Itis thus shown that gene interactions can be modeled as a multi-dimensionalalgebra, and that only two interacting genes are sufficientfor (i) complex pattern formation, (ii) chaotic differentiationbehavior, and (iii) production of sharp edges from a continuouspositional information field. This model is meant to elucidatethe properties of the process of positional information-guidedbiomorphogenesis, not to serve as a simulation of any particularorganism's development. Good quantitative data are not currentlyavailable on the interplay of gene products in morphogenesis.Thus, no attempt is made to link the images produced with actualpictures of any particular real organism. A brief introductionto top-down models and positional information is followed bythe formal definition of the model. Then, the implications ofthe resulting morphologies to biological development are discussed,in terms of static shapes, parametrization studies, time series(movies made from individual frames), and behavior of the modelin light of experimental perturbations. All figures (in grayscale),formulas and parameter values needed to re-create the figuresand movies are included.