Stimulation of the growth and solamargine production by Solanum paludosum multiple shoot cultures using a new culture medium

Organogenic callus cultures of Solanum paludosum were obtained from root, hypocotyle and cotyledon explants of plantlets cultured in sterile conditions. These callus cultures developed multiple shoots which proliferated in Murashige and Skoog basal liquid medium. These multiple shoots produced solamargine, the main steroidal glycoalkaloid present in the unripe fruits.The optimization of the macronutrient composition of the liquid medium was performed by a method derived from the plant composition. This approach results in the establishment of an appropriate medium (SPOM medium) suitable for the improvement of both growth and solamargine production by multiple shoot cultures of S. paludosum.     

Predicting badger sett numbers: evaluating methods in East Sussex

Abstract. One way in which a species' numbers may be estimated without direct counting is to predict their dispersion and density from more readily available habitat measures, such as landscape variables measured from maps or vegetation variables measured in the field. We compare the power of ordination and regression techniques for predicting badger ( Meles meles L.) numbers at a local scale, using a land class system, map-read landscape variables and field-derived vegetation variables. Sett density was used as a surrogate of badger density. Multiple linear regression using vegetation and landscape variables together gave the most accurate prediction of sett density, while ordination techniques were of lesser value. The addition of vegetation variables to landscape variables did not substantially improve the power of ordination. Outlier Sett Density was predicted more accurately, and by different variables, to Main Sett Density. The relationship between badger ecology and habitat variables that were useful in predicting sett density is discussed.     

Ecological optima and tolerances of Thelypteris limbosperma,Athyrium distentifolium,and Matteuccia struthiopteris along environmental gradients in Western Norway

The distribution and abundance of Thelypteris limbosperma, Athyrium distentifolium, and Matteuccia struthiopteris are modelled statistically in relation to 14 environmental variables along the major climatic, topographic, and edaphic gradients in western Norway. The data are from 624 stands from which measurements or estimates of mean January and mean July temperatures, humidity, altitude, aspect, and slope are available. From 182 of these stands eight soil variables have also been measured. The species responses are quantified by two numerical methods: Gaussian logit regression and weighted averaging (WA) regression. The estimated WA optima suggest that A. distentifolium has an ecological preference for low July and January temperatures, high altitudes, and soils of low-medium pH and base content. The species shows statistically significant Gaussian responses with summer temperature, humidity (= Martonnes humidity index), altitude, slope, aspect, pH, cation exchange capacity, and base saturation with optima of 8.7 °C, 188.9, 1220 m, 28°, 29°, 4.8, 13.77 mEq 100 g dry soil^-1, and 13.4%, respectively. These suggest that the occurrence and relative abundance of A. distentifolium are well predicted by summer temperature, topography, and soil pH and base status. T. limbosperma has WA optima that suggest that it favours moderately high winter and summer temperatures, high humidity, medium altitude, and soils of low pH and base content. It has significant Gaussian responses to summer temperature (optimum =12.6 °C), winter temperature (-1.8 °C), humidity (179.2), altitude (459.5 m), slope (22.5°), and Na (0.7 mg 100 g dry soil^-1). These suggest that climatic factors, altitude, and slope are significant predictors for its occurrence and abundance. M. struthiopteris has high WA optima for summer temperature, pH, Ca, Mg, K, Na, cation exchange capacity (CEC), and base saturation, and a low optima for humidity and winter temperature. Of these, summer temperature (16.0 °C), Ca (63.1 mg 100 g dry soil^-1), Mg (41.0 mg 100 g dry soil^-1), K (23.6 mg 100 g dry soil^-1), Na (5.0 mg 100 g dry soil^-1), CEC (60.7 mEq 100 g dry soil^-1), and base saturation (56.3%) have significant Gaussian logit responses, as do aspect (150.2°) and loss-on-ignition (9.4%). These results suggest that the occurrence and relative abundance of M. struthiopteris are well predicted by high soil base cations, a generally southern aspect, low organic content in the soil, and high July temperatures.     

Genetic analysis of agronomic traits in a cross between sugarcane (Saccharum officinarum L.) and its presumed progenitor (S. robustum Brandes & Jesw. ex Grassl)

Saccharum robustum Brandes & Jesw. ex Grassl has been suggested as the immediate progenitor species of cultivated sugarcane (S. officinarum L.) [4]. Chromosome pairing and assortment in these two species were previously studied by genetic analysis of single-dose DNA markers in parents in and 44 F₁ progeny of a cross between euploid, meiotically regular 2n=80S. officinarum LA Purple andS. robustum Mol 5829 [2]. This same population was subsequently clonally propagated and evaluated in replicated trials for quantitative traits important to sugarcane breeders. Numbers of stalks, tasseled stalks, and stalks with smut, and the average diameter of two stalks were determined one day prior to harvest. At harvest, plant material from each plot was weighed and evaluated for pol (sucrose content) and fiber percentages. Clones were significantly different (P<0.01) for all traits analyzed. Associations of 83 single-dose arbitrarily primed PCR genetic markers with quantitative trait loci (QTL) of recorded traits was determined by single-factor ANOVA, and multiple regression. QTL analysis revealed markers significantly (P<0.05) associated with the expression of each trait analyzed. Markers associated with QTL after multiple regression were tested for digenic linear × linear epistatic interactions. The various multilocus models explained between 23% and 58% of the total phenotypic variation and 32% and 76% of the genotypic variation for the various traits. Digenic interactions were uncommon. Implications for marker-assisted selection in sugarcane and sugarcane domestication are discussed.     

Multiple peptide synthesis

The synthesis of large numbers of peptides can be very labor intensive and, if a conventional peptide synthesizer is used, only small numbers of peptides can be produced within a reasonable time. The techniques described below can make large numbers of different peptides simultaneously with varying degrees of mechanization, ranging from the wholly manual methods, to those involving complete mechanization of the whole synthesis process. Most of the multiple synthesis methods are primarily intended for small scale production ranging from microgram amounts up to a few tens of milligrams. All of the systems are economical in use of solvents and reagents, enabling cost-effective synthesis. The techniques described can also be used to prepare peptide libraries, containing several millions of peptide sequences, to enable the rapid screening of all possible permutations of amino acids within short peptides. However, it is considered that multiple synthesis methods are not particularly suited where extreme high purity or very long peptides are required.     

Rapid screening for metabolite overproduction in fermentor broths, using pyrolysis mass spectrometry with multivariate calibration and artificial neural networks

Binary mixtures of model systems consisting of the antibiotic ampicillin with either Escherichia coli or Staphylococcus auresu were subjected to pyrolysis mass spectrometry (PyMS). To deconvolute the pyrolysis mass spectra, so as to obtain quantitative information on the concentration of ampicilin in the mixtures, partial least squares regression (PLS), principal components regression (PCR), and fully interconnected feedforward artificial neural networks (ANNs) were studied. In the latter case, the weights were modified using the standard backpropagation algorithm, and the nodes used a sigmoidal squsahing funciton. It was found that each of the methods could be used to provide calibration models which gave excellent predictions for the concentrations of ampicillin in samples on which they had not been trained. Furthermore, ANNs trained to predict the amount of ampicilin in E. coli were able to generalise so as to predict the concentration of ampicillin in a S. aureus background, illustrating the robustness of ANNs to rather substantial variations in the biological background. The PyMS of the complex mixture of ampicilin in bacteria could not be expressed simply in terms of additive combinations of the spectra describing the pure components of the mixtures and their relative concentrations. Intermolecular reactions took place in the pyrolysate, leading to a lack of superposition of the spectral components and to a dependence of the normalized mass spectrum on sample size. Samples from fermentations of a single organism in a complex production medium were also analyzed quantitatively for a drug of commercial interest. The drug could also be quantified in a variety of mutant-producing strains cultivated in the same medium. The combination of PyMS and ANNs constitutes a novel, rapid, and convenient method for exploitation in strain improvement screening programs. (c) 1994 John Wiley & Sons, Inc.