INTERACTION OF IONIZING AND VISIBLE RADIATION IN MUTATION INDUCTION IN NEUROSPORA CRASSA

Klein , Richard M. (New York Bot. Gdn., New York, N.Y.), and Deana T. Klein. Interaction of ionizing and visible radiation in mutation induction in Neurospora crassa. Amer. Jour. Bot. 49(8): 870–874. 1962.—Conidia of the purple adenineless strain of N. crassa were irradiated with 25 kr of X rays and then exposed to far-red or red radiations or to far-red followed by red radiation. Far-red light, without effect on un-irradiated conidia, augmented the genetic damage caused by X rays as measured by survival (colony count), back mutation to adenine prototrophy, and the induction of mutants affecting colony morphology. Post-X-irradiation with red light ameliorated the severity of X-radiation as measured by survival and back mutation. The potentiation of X-ray-induced genetic damage by far-red light could be completely negated by subsequent exposure to red light.     

Inactivation of rat pineal hydroxyindole-O-methyltransferase by disulfide-containing compounds

Rat pineal hydroxyindole-O-methyltransferase activity in crude homogenates is reduced by treatment with disulfides. Cystamine (IC50 = 128 microM) and selenocystamine (IC50 = 13 microM) are the most potent compounds tested. Reduced cystamine (cysteamine) and diaminohexane are inactive. N,N'-Diacetylcystamine, penicillamine disulfide, and glutathione disulfide are less potent or inactive; but several peptides (oxytocin, vasopressin, and arginine vasotocin) are active. Inactivation by cystamine is time- and temperature-dependent and is accelerated at higher pH. Disulfide treatment of intact pinealocytes also inactivates the enzyme. Addition of dithiothreitol during the enzyme assay completely reactivates inactivated enzyme formed by disulfide treatment of homogenates or intact cells. Rat hydroxyindole-O-methyltransferase is also inactivated in the absence of added disulfides and dissolved O2. This spontaneous inactivation is time-, temperature-, and pH-dependent and can be completely prevented, but not reversed, by dithiothreitol. In contrast to the inhibitory effects of cystamine on the rat enzyme, cystamine does not alter bovine hydroxyindole-O-methyltransferase and increases ovine hydroxyindole-O-methyltransferase activity. The bovine and ovine enzymes do not become inactive in the absence of added disulfides. Together these observations indicate that rat pineal hydroxyindole-O-methyltransferase can be inactivated by a protein thiol:disulfide exchange mechanism. This mechanism may contribute to the physiological regulation of this enzyme in the rat pineal gland but does not appear to be a common feature of pineal hydroxyindole-O-methyltransferase regulation in all species.     

Intraspecific genetic variation of a Fagus sylvatica population in a temperate forest derived from airborne imaging spectroscopy time series

1. The growing pace of environmental change has increased the need for large‐scale monitoring of biodiversity. Declining intraspecific genetic variation is likely a critical factor in biodiversity loss, but is especially difficult to monitor: assessments of genetic variation are commonly based on measuring allele pools, which requires sampling of individuals and extensive sample processing, limiting spatial coverage. Alternatively, imaging spectroscopy data from remote platforms may hold the potential to reveal genetic structure of populations. In this study, we investigated how differences detected in an airborne imaging spectroscopy time series correspond to genetic variation within a population of Fagus sylvatica under natural conditions.
2. We used multi‐annual APEX (Airborne Prism Experiment) imaging spectrometer data from a temperate forest located in the Swiss midlands (Laegern, 47°28'N, 8°21'E), along with microsatellite data from F. sylvatica individuals collected at the site. We identified variation in foliar reflectance independent of annual and seasonal changes which we hypothesize is more likely to correspond to stable genetic differences. We established a direct connection between the spectroscopy and genetics data by using partial least squares (PLS) regression to predict the probability of belonging to a genetic cluster from spectral data.
3. We achieved the best genetic structure prediction by using derivatives of reflectance and a subset of wavebands rather than full‐analyzed spectra. Our model indicates that spectral regions related to leaf water content, phenols, pigments, and wax composition contribute most to the ability of this approach to predict genetic structure of F. sylvatica population in natural conditions.
4. This study advances the use of airborne imaging spectroscopy to assess tree genetic diversity at canopy level under natural conditions, which could overcome current spatiotemporal limitations on monitoring, understanding, and preventing genetic biodiversity loss imposed by requirements for extensive in situ sampling.

     

Molecular alteration of a muscarinic acetylcholine receptor system during synaptogenesis

Biochemical properties of the muscarinic acetylcholine receptor system of the avian retina were found to change during the period when synapses form in ovo. Comparison of ligand binding to membranes obtained before and after synaptogenesis showed a significant increase in the affinity, but not proportion, of the high affinity agonist-binding state. There was no change in receptor sensitivity to antagonists during this period. Pirenzepine binding, which can discriminate muscarinic receptor subtypes, showed the presence of a single population of low affinity sites (M2) before and after synaptogenesis. The change in agonist binding was not due to the late development of receptor function; tests for receptor-stimulated phosphatidylinositol turnover and for modulation of agonist binding by guanylylimidodiphosphate showed functional coupling to be present several days prior to the onset of synapse formation. However, detergent-solubilization of membranes eliminated differences in agonist binding between receptors from embryos and hatched chicks, suggesting a developmental change in interactions of the receptor with functionally related membrane components. A possible basis for altered interactions was obtained from isoelectric point data showing that the muscarinic receptor population underwent a transition from a predominantly low pI form (4.25) in 13 day embryos to a predominantly high pI form (4.50) in newly hatched chicks. The possibility that biochemical changes in the muscarinic receptor play a role in differentiation of the system by controlling receptor position on the surface of nerve cells is discussed.     

State-of-the art data normalization methods improve NMR-based metabolomic analysis

Extracting biomedical information from large metabolomic datasets by multivariate data analysis is of considerable complexity. Common challenges include among others screening for differentially produced metabolites, estimation of fold changes, and sample classification. Prior to these analysis steps, it is important to minimize contributions from unwanted biases and experimental variance. This is the goal of data preprocessing. In this work, different data normalization methods were compared systematically employing two different datasets generated by means of nuclear magnetic resonance (NMR) spectroscopy. To this end, two different types of normalization methods were used, one aiming to remove unwanted sample-to-sample variation while the other adjusts the variance of the different metabolites by variable scaling and variance stabilization methods. The impact of all methods tested on sample classification was evaluated on urinary NMR fingerprints obtained from healthy volunteers and patients suffering from autosomal polycystic kidney disease (ADPKD). Performance in terms of screening for differentially produced metabolites was investigated on a dataset following a Latin-square design, where varied amounts of 8 different metabolites were spiked into a human urine matrix while keeping the total spike-in amount constant. In addition, specific tests were conducted to systematically investigate the influence of the different preprocessing methods on the structure of the analyzed data. In conclusion, preprocessing methods originally developed for DNA microarray analysis, in particular, Quantile and Cubic-Spline Normalization, performed best in reducing bias, accurately detecting fold changes, and classifying samples.