Differentiation of intestinal spirochaetes by multilocus enzyme electrophoresis analysis and 16S rRNA sequence comparisons

Abstract Multilocus enzyme electrophoresis (MEE) analysis and comparisons of nearly complete 16S rRNA gene sequences (1416 nucleotide positions) were used to evaluate phylogenetic relationships among Serpulina hyodysenteriae strain B78^T, S. innocens strain B256^T, Brachyspira aalborgi strain 513A^T, and eight uncharacterised strains of swine, avian, and human intestinal spirochaetes. From MEE analysis, nine strains could be assigned to five groups containing other intestinal spirochaetes ( genetic distances between groups = 0.6–0.9). Chicken spirochaete strain C1 and B. aalborgi 513A^T represented unique electrophoretic types and formed their own MEE groups. Despite MEE differences, the 11 strains had highly similar (96.3–99.9%) 16S rRNA sequences. These findings point out limitations of both MEE analysis and 16S rRNA sequence comparisons when used as solitary techniques for classifying intestinal spirochaetes related to Brachyspira/ Serpulina species.     

Elemental Markers in Elasmobranchs: Effects of Environmental History and Growth on Vertebral Chemistry

Differences in the chemical composition of calcified skeletal structures (e.g. shells, otoliths) have proven useful for reconstructing the environmental history of many marine species. However, the extent to which ambient environmental conditions can be inferred from the elemental signatures within the vertebrae of elasmobranchs (sharks, skates, rays) has not been evaluated. To assess the relationship between water and vertebral elemental composition, we conducted two laboratory studies using round stingrays, Urobatis halleri, as a model species. First, we examined the effects of temperature (16°, 18°, 24°C) on vertebral elemental incorporation (Li/Ca, Mg/Ca, Mn/Ca, Zn/Ca, Sr/Ca, Ba/Ca). Second, we tested the relationship between water and subsequent vertebral elemental composition by manipulating dissolved barium concentrations (1x, 3x, 6x). We also evaluated the influence of natural variation in growth rate on elemental incorporation for both experiments. Finally, we examined the accuracy of classifying individuals to known environmental histories (temperature and barium treatments) using vertebral elemental composition. Temperature had strong, negative effects on the uptake of magnesium (D_Mg) and barium (D_Ba) and positively influenced manganese (D_Mn) incorporation. Temperature-dependent responses were not observed for lithium and strontium. Vertebral Ba/Ca was positively correlated with ambient Ba/Ca. Partition coefficients (D_Ba) revealed increased discrimination of barium in response to increased dissolved barium concentrations. There were no significant relationships between elemental incorporation and somatic growth or vertebral precipitation rates for any elements except Zn. Relationships between somatic growth rate and D_Zn were, however, inconsistent and inconclusive. Variation in the vertebral elemental signatures of U. halleri reliably distinguished individual rays from each treatment based on temperature (85%) and Ba exposure (96%) history. These results support the assumption that vertebral elemental composition reflects the environmental conditions during deposition and validates the use of vertebral elemental signatures as natural markers in an elasmobranch. Vertebral elemental analysis is a promising tool for the study of elasmobranch population structure, movement, and habitat use.     

Benzothienyloxy phenylpropanamines, novel dual inhibitors of serotonin and norepinephrine reuptake

A series of benzothienyloxy propylamines have been prepared and are demonstrated to be inhibitors of both serotonin and norepinephrine reuptake.     

Support vector machines for separation of mixed plant-pathogen EST collections based on codon usage

MOTIVATION: Discovery of host and pathogen genes expressed at the plant-pathogen interface often requires the construction of mixed libraries that contain sequences from both genomes. Sequence identification requires high-throughput and reliable classification of genome origin. When using single-pass cDNA sequences difficulties arise from the short sequence length, the lack of sufficient taxonomically relevant sequence data in public databases and ambiguous sequence homology between plant and pathogen genes. RESULTS: A novel method is described, which is independent of the availability of homologous genes and relies on subtle differences in codon usage between plant and fungal genes. We used support vector machines (SVMs) to identify the probable origin of sequences. SVMs were compared to several other machine learning techniques and to a probabilistic algorithm (PF-IND) for expressed sequence tag (EST) classification also based on codon bias differences. Our software (Eclat) has achieved a classification accuracy of 93.1% on a test set of 3217 EST sequences from Hordeum vulgare and Blumeria graminis, which is a significant improvement compared to PF-IND (prediction accuracy of 81.2% on the same test set). EST sequences with at least 50 nt of coding sequence can be classified using Eclat with high confidence. Eclat allows training of classifiers for any host-pathogen combination for which there are sufficient classified training sequences. AVAILABILITY: Eclat is freely available on the Internet (http://mips.gsf.de/proj/est) or on request as a standalone version. CONTACT: friedel@informatik.uni-muenchen.de.