Levels of genetic polymorphism: marker loci versus quantitative traits.

Species are the units used to measure ecological diversity and alleles are the units of genetic diversity. Genetic variation within and among species has been documented most extensively using allozyme electrophoresis. This reveals wide differences in genetic variability within, and genetic distances among, species, demonstrating that species are not equivalent units of diversity. The extent to which the pattern observed for allozymes can be used to infer patterns of genetic variation in quantitative traits depends on the forces generating and maintaining variability. Allozyme variation is probably not strictly neutral but, nevertheless, heterozygosity is expected to be influenced by population size and genetic distance will be affected by time since divergence. The same is true for quantitative traits influenced by many genes and under weak stabilizing selection. However, the limited data available suggest that allozyme variability is a poor predictor of genetic variation in quantitative traits within populations. It is a better predictor of general phenotypic divergence and of postzygotic isolation between populations or species, but is only weakly correlated with prezygotic isolation. Studies of grasshopper and planthopper mating signal variation and assortative mating illustrate how these characters evolve independently of general genetic and morphological variation. The role of such traits in prezygotic isolation, and hence speciation, means that they will contribute significantly to the diversity of levels of genetic variation within and among species.     

Peanut (Arachis hypogaea) lectin recognizes α-linked galactose, but not N-acetyl lactosamine in N-linked oligosaccharide terminals

Peanut (Arachis hypogaea) agglutinin (PNA) is extensively used as tumour marker as it strongly recognises the cancer specific T antigen (Galβ1→3GalNAc-), but not its sialylated version. However, an additional specificity towards Galβ1→4GlcNAc (LacNAc), which is not tumour specific, had been attributed to PNA. For correct interpretation of lectin histochemical results we examined PNA sugar specificity using naturally occurring or semi-synthetic glycoproteins, matrix-immobilised galactosides and lectin-binding tissue glycoproteins, rather than mono- or disaccharides as ligands. Dot-blots, transfer blots or polystyrene plate coatings of the soluble glycoconjugates were probed with horse-radish peroxidase (HRP) conjugates of PNA and other lectins of known specificity. Modifications of PNA-binding glycoproteins, including selective removal of O-linked oligosaccharides and treatment with glycosidases revealed that Galβ1→4GlcNAc (LacNAc) was ineffective while terminal α-linked galactose (TAG) as well as exposed T antigen (Galβ1→3 GalNAc-) was excellent as sugar moiety in glycoproteins for their recognition by PNA. When immobilised, melibiose was superior to lactose in PNA binding. Results were confirmed using TAG-specific human serum anti-α-galactoside antibody.     

Rapid, simple and sensitive high-performance liquid chromatographic method for detection and determination of acyclovir in human plasma and its use in bioavailability studies

A rapid, simple and sensitive reversed-phase high-performance liquid chromatographic (HPLC) method has been developed for the measurement of acyclovir concentrations in human plasma and its use in bioavailability studies is evaluated. Unchanged acyclovir has been quantified without the introduction of an internal standard using the present method. Human plasma proteins were selectively precipitated by the addition of 7% perchloric acid to spiked plasma samples or to the plasma samples obtained after acyclovir administration to human volunteers and the mixture was spun at 1000 g for 10 min. The supernatant was directly injected into a Novaflex C₁₈ column and detected at 254 nm. The mobile phase consisted of octane sulfonic acid buffer (pH 2.5) and methanol (92:08). The limit of quantitation for acyclovir in plasma was 20 ng/ml, which enabled the determination of the area under the curve (AUC) more precisely, that is, it is much closer to its extrapolated value. The present method has been successfully applied to samples from bioavailability studies.