Rapid identification of precursor cDNAs encoding five structural classes of antimicrobial peptides from pickerel frog (Rana palustris) skin secretion by single step “shotgun” cloning.

The skin secretion of the North American pickerel frog (Rana palustris) has long been known to have pronounced noxious/toxic properties and to be highly effective in defence against predators and against other sympatric amphibians. As it consists largely of a complex mixture of peptides, it has been subjected to systematic peptidomic study but there has been little focus on molecular cloning of peptide-encoding cDNAs and by deduction, the biosynthetic precursors that they encode. Here, we demonstrate that the cDNAs encoding the five major structural families of antimicrobial peptides can be elucidated by a single step “shotgun” cloning approach using a cDNA library constructed from the source material of the peptidomic studies—the defensive skin secretion itself. Using a degenerate primer pool designed to a highly conserved nucleic acid sequence 5' to the initiation codon of known antimicrobial peptide precursor transcripts, we amplified cDNA sequences representing five major classes of antimicrobial peptides, such as esculentins, brevinins, ranatuerins, palustrins and temporins. Bioinformatic comparisons of precursor open-reading frames and nucleic acid sequences revealed high degrees of structural similarities between analogous peptides of R. palustris and the Chinese bamboo odorous frog, Rana versabilis. This approach thus constitutes a robust technique that can be used either alone or ideally, in parallel with peptidomic analysis of skin secretion, to rapidly extract primary structural information on amphibian skin secretion peptides and their biosynthetic precursors.

Noise resilience and entanglement evolution in two nonequivalent classes of quantum algorithms

The speedup provided by quantum algorithms with respect to their classical counterparts is at the origin of scientific interest in quantum computation. However, the fundamental reasons for such a speedup are not yet completely understood and deserve further attention. In this context, the classical simulation of quantum algorithms is a useful tool that can help us in gaining insight. Starting from the study of general conditions for classical simulation, we highlight several important differences between two nonequivalent classes of quantum algorithms. We investigate their performance under realistic conditions by quantitatively studying their resilience with respect to static noise. This latter refers to errors affecting the initial preparation of the register used to run an algorithm. We also compare the evolution of the entanglement involved in the different computational processes.

Novel linkage to chromosome 20p using latent classes of psychotic illness in 270 Irish high-density families

Background: Several lines of evidence suggest that the clinical heterogeneity of schizophrenia is due to genetic heterogeneity. Genetic heterogeneity may decrease the signal-to-noise ratio in linkage and association studies. Therefore, linkage studies of clinically homogeneous classes of psychotic illness may result in greater power to detect at least some loci.