Human Menkes X-chromosome disease and the staphylococcal cadmium-resistance ATPase: a remarkable similarity in protein sequences

A search with the proposed amino acid translation product from the new ‘candidate gene’ for human Menkes disease against protein sequence libraries showed a remarkable similarity to that for the cadmium efflux ATPase from Staphylococcus aureus resistance plasmids. The Menkes sequence appears closer to the CadA Cd²⁺ sequence than to P-type ATPases from animal sources. Menkes syndrome is an X-chromosome invariably fatal disease that results from abberant copper metabolism. The gene that is defective in Menkes patients, i.e. the Menkes candidate gene, encodes a P-type ATPase, whose properties satisfactorily explain the phenotype of the disease. P-type ATPases are all cation pumps, either for uptake (e.g. the bacterial Kdp K⁺ ATPase), for efflux (e.g. the muscle sarcoplasmic reticulum Ca²⁺ ATPase), or for cation exchange (e.g. the animal cell Na⁺/K⁺ ATPase). These enzymes have a conserved aspartate residue that is transiently phosphorylated from ATP during the transport cycle, hence the name ‘P-type’ ATPase. The Menkes sequence shares with the staphylococcal CadA ATPase those regions common to all P-type ATPases and also an N-terminal dithiol region that was proposed to be a ‘metal-binding motif’. There are one or two copies of this motif in the available CadA sequences and six copies in the Menkes sequence.     

The caecilian amphibian Scolecomorphus kirkii Boulenger as prey of the burrowing asp Atractaspis aterrima Günther: trophic relationships of fossorial vertebrates

A report is given of an adult caecilian, Scolecomorphus kirkii, found in the gut of a specimen of the snake Atractaspis aterrima from the Udzungwa Mountains, Tanzania. Both predator and prey are largely fossorial in soil, and their ecology is poorly known, such that this is the first reported predator of any scolecomorphid caecilian. The caecilian was ingested head first and much of the flesh from the anterior of the specimen had been digested. The prey/predator mass ratio is 0.48. This value is substantially higher than reported for A. aterrima from West Africa, and refutes the notion that this species feeds only on small prey. Most reported predators of caecilians are snakes, and a brief review is presented.     

Spatial ecology of golden jackal in farmland in the Ethiopian Highlands

The spatial ecology of golden jackal Canis aureus was studied on farmland adjacent to the Bale Mountains National Park in southern Ethiopia during 1998–2000. Three adult and four subadult jackals were captured in leg‐hold traps and radiotagged. The range size of the adult jackals varied from 7.9 to 48.2 km² and the subadults from 24.2 to 64.8 km² . These ranges are the largest recorded for this species. Range overlap of the tagged jackals averaged 54%, which, in conjunction with observations of associations between individuals, suggested that all the tagged jackals belonged to one social group. Tagged jackals were observed alone on 87% of occasions despite the extensive overlap in individual ranges. Pairs consisting of a male and female were the most commonly observed group and larger groups were seen on only five occasions. Jackals in this population appeared less gregarious than observed elsewhere. The jackals used all the habitats available to them, particularly at night when they foraged in Artemesia and Hypericum bush and farmland. During the day they were more frequently found in Hagenia and Juniper woodland and their diurnal resting sites were characterized by thick cover. This is the first detailed study of golden jackals in a human‐modified landscape in Africa and further demonstrates the flexibility in behaviour and ecology exhibited by this species throughout its range.     

Estimating dataset size requirements for classifying DNA microarray data.

A statistical methodology for estimating dataset size requirements for classifying microarray data using learning curves is introduced. The goal is to use existing classification results to estimate dataset size requirements for future classification experiments and to evaluate the gain in accuracy and significance of classifiers built with additional data. The method is based on fitting inverse power-law models to construct empirical learning curves. It also includes a permutation test procedure to assess the statistical significance of classification performance for a given dataset size. This procedure is applied to several molecular classification problems representing a broad spectrum of levels of complexity.     

Continuous representations of time-series gene expression data.

We present algorithms for time-series gene expression analysis that permit the principled estimation of unobserved time points, clustering, and dataset alignment. Each expression profile is modeled as a cubic spline (piecewise polynomial) that is estimated from the observed data and every time point influences the overall smooth expression curve. We constrain the spline coefficients of genes in the same class to have similar expression patterns, while also allowing for gene specific parameters. We show that unobserved time points can be reconstructed using our method with 10-15% less error when compared to previous best methods. Our clustering algorithm operates directly on the continuous representations of gene expression profiles, and we demonstrate that this is particularly effective when applied to nonuniformly sampled data. Our continuous alignment algorithm also avoids difficulties encountered by discrete approaches. In particular, our method allows for control of the number of degrees of freedom of the warp through the specification of parameterized functions, which helps to avoid overfitting. We demonstrate that our algorithm produces stable low-error alignments on real expression data and further show a specific application to yeast knock-out data that produces biologically meaningful results.     

Manipulating photosynthesis

The levels of individual photosynthetic proteins can be independently decreased by theAgrobacterium-mediated transformation of plants with antisens RNA constructs. Protocols for the introduction of such constructs intoAgrobacterium, theAgrobacterium-mediated transformation of tobacco leaf disks, and the screening and analysis of the transgenic plants produced are described.     

Growth limitation of planktonic bacteria in a large mesotrophic lake

We studied nutrient-limitation of bacterioplankton growth in Lake Constance, a mesotrophic lake, between February and August in 1992. We amended 1-m filtrates with a single nutrient or nutrient combinations at 5 or 10 m final concentration, and the limiting nutrient or nutrient combination was inferred from the assay in which bacterial growth was most stimulated. The following nutrients were added individually or in combination: glucose, amino acids, peptone, and ammonium as C and N sources, and inorganic phosphate. From January until the beginning of the phytoplankton spring bloom in mid-April, C alone was growth-limiting. During the spring bloom a complex growth-limitation pattern occurred; first P was limiting, then for only 1 week C + N together, and thereafter P + C. During the clear-water phase with very low chlorophyll concentrations, P + C together limited bacterial growth again, interrupted by a period when C + N + P shortage caused a triple limitation. Later in the season, P + C were growth-limiting again. The growth efficiency (bacterial biomass produced/substrates used) on the basis of amino acid and carbohydrate used varied between 17 and 35%. The addition of various C and N sources indicated that the growth efficiency strongly depended on the quality of the substrates and the adaptation of the bacterial assemblages, for example, whether C and N originated from amino acids or glucose and ammonium.