Structural and Functional Characterization of an Anesthetic Binding Site in the Second Cysteine-Rich Domain of Protein Kinase Cδ?

Elucidating the principles governing anesthetic-protein interactions requires structural determinations at high resolutions not yet achieved with ion channels. Protein kinase C (PKC) activity is modulated by general anesthetics. We solved the structure of the phorbol-binding domain (C1B) of PKCδ complexed with an ether (methoxymethylcycloprane) and with an alcohol (cyclopropylmethanol) at 1.36-Å resolution. The cyclopropane rings of both agents displace a single water molecule in a surface pocket adjacent to the phorbol-binding site, making van der Waals contacts with the backbone and/or side chains of residues Asn-237 to Ser-240. Surprisingly, two water molecules anchored in a hydrogen-bonded chain between Thr-242 and Lys-260 impart elasticity to one side of the binding pocket. The cyclopropane ring takes part in π-acceptor hydrogen bonds with the amide of Met-239. There is a crucial hydrogen bond between the oxygen atoms of the anesthetics and the hydroxyl of Tyr-236. A Tyr-236-Phe mutation results in loss of binding. Thus, both van der Waals interactions and hydrogen-bonding are essential for binding to occur. Ethanol failed to bind because it is too short to benefit from both interactions. Cyclopropylmethanol inhibited phorbol-ester-induced PKCδ activity, but failed to do so in PKCδ containing the Tyr-236-Phe mutation.     

Changes in sperm parameters of sex-reversed female rainbow trout during spawning season in relation to sperm parameters of normal males

The production of all-female populations has important economic benefits in commercial rainbow trout aquaculture. The procedure commonly implemented to produce all-female stocks centers on the sex reversal of rainbow trout females via the administration of androgens in the early developmental stages, followed by the egg fertilization of normal females with semen from sex-reversed females (srf). However, there is no information regarding the quality of semen from srf rainbow trout throughout the spawning season. This information is critical because the quality of srf semen is highly variable. The aim of the study was to determine the changes in the semen parameters of srf rainbow trout throughout the duration of the spawning season. Sperm concentration, sperm motility parameters, and the biochemical parameters of seminal plasma (protein concentration, antitrypsin activity, osmolality, and lactate dehydrogenase activity) from srf were monitored during the spawning season and compared with normal male rainbow trout. The observed values of sperm, protein concentration, antitrypsin activity, osmolality, and lactate dehydrogenase activity of seminal plasma were all higher in comparison with normal males. Semen from srf was therefore characterized by a lower sperm motility during each period of the spawning season, in comparison with normal males, approximately 1.8, 1.5, and 1.7 times, respectively for the beginning, middle, and end of the spawning season. The percentage of sperm motility from srf and normal males were affected by the spawning season in the same way, as the highest values in the middle of the spawning season demonstrate (60% and 91% for srf and normal males, respectively). Spermatozoa of srf are characterized by a lower speed and a more curvilinear trajectory of movement as compared with that of normal males. The patterns of changes during the spawning season in sperm concentration, sperm motility parameters, as well as osmolality, and lactate dehydrogenase activity of the seminal plasma of srf were different in comparison with normal males. Our results could be important for fish breeders in regard to the spawning control of srf rainbow trout, as well as for the development of short- and long-term sperm storage procedures.     

Development of novel low-copy nuclear markers for Hieraciinae (Asteraceae) and their perspective for other tribes

? Premise of the study: The development of three low-copy nuclear markers for low taxonomic level phylogenies in Asteraceae with emphasis on the subtribe Hieraciinae is reported. ? Methods and Results: Marker candidates were selected by comparing a Lactuca complementary DNA (cDNA) library with public DNA sequence databases. Interspecific variation and phylogenetic signal of the selected genes were investigated for diploid taxa from the subtribe Hieraciinae and compared to a reference phylogeny. Their ability to cross-amplify was assessed for other Asteraceae tribes. All three markers had higher variation (2.1-4.5 times) than the internal transcribed spacer (ITS) in Hieraciinae. Cross-amplification was successful in at least seven other tribes of the Asteraceae. Only three cases indicating the presence of paralogs or pseudogenes were detected. ? Conclusions: The results demonstrate the potential of these markers for phylogeny reconstruction in the Hieraciinae as well as in other Asteraceae tribes, especially for very closely related species.     

Identification and methicillin resistance of coagulase-negative staphylococci isolated from nasal cavity of healthy horses

The aim of this study was an analysis of the staphylococcal flora of the nasal cavity of 42 healthy horses from 4 farms, along with species identification of CoNS isolates and determination of resistance to 18 antimicrobial agents, particularly phenotypic and genotypic methicillin resistance. From the 81 swabs, 87 staphylococci were isolated. All isolates possessed the gap gene but the coa gene was not detected in any of these isolates. Using PCR-RFLP of the gap gene, 82.8% of CoNS were identified: S. equorum (14.9%), S. warneri (14.9%), S. sciuri (12.6%), S. vitulinus (12.6%), S. xylosus (11.5%), S. felis (5.7%), S. haemolyticus (3.4%), S. simulans (3.4%), S. capitis (1.1%), S. chromogenes (1.1%), and S. cohnii subsp. urealyticus (1.1%). To our knowledge, this was the first isolation of S. felis from a horse. The species identity of the remaining Staphylococcus spp. isolates (17.2%) could not be determined from the gap gene PCR-RFLP analysis and 16S rRNA gene sequencing data. Based on 16S-23S intergenic transcribed spacer PCR, 11 different ITS-PCR profiles were identified for the 87 analyzed isolates. Results of API Staph were consistent with molecular identification of 17 (19.5%) isolates. Resistance was detected to only 1 or 2 of the 18 antimicrobial agents tested in the 17.2% CoNS isolates, including 6.9% MRCoNS. The mecA gene was detected in each of the 5 (5.7%) phenotypically cefoxitin-resistant isolates and in 12 (13.8%) isolates susceptible to cefoxitin. In total, from 12 horses (28.6%), 17 (19.5%) MRCoNS were isolated. The highest percentage of MRCoNS was noted among S. sciuri isolates (100%).     

Sequence fingerprints of enzyme specificities from the glycoside hydrolase family GH57

The glycoside hydrolase family 57 (GH57) contains five well-established enzyme specificities: α-amylase, amylopullulanase, branching enzyme, 4-α-glucanotransferase and α-galactosidase. Around 700 GH57 members originate from Bacteria and Archaea, a substantial number being produced by thermophiles. An intriguing feature of family GH57 is that only slightly more than 2 % of its members (i.e., less than 20 enzymes) have already been biochemically characterized. The main goal of the present bioinformatics study was to retrieve from databases, and analyze in detail, sequences having clear features of the five GH57 enzyme specificities mentioned above. Of the 367 GH57 sequences, 56 were evaluated as α-amylases, 99 as amylopullulanases, 158 as branching enzymes, 46 as 4-α-glucanotransferases and 8 as α-galactosidases. Based on the analysis of collected sequences, sequence logos were created for each specificity and unique sequence features were identified within the logos. These features were proposed to define the so-called sequence fingerprints of GH57 enzyme specificities. Domain arrangements characteristic of the individual enzyme specificities as well as evolutionary relationships within the family GH57 are also discussed. The results of this study could find use in rational protein design of family GH57 amylolytic enzymes and also in the possibility of assigning a GH57 specificity to a hypothetical GH57 member prior to its biochemical characterization.     

Additional contribution of emerging risk factors to the prediction of the risk of type 2 diabetes: evidence from the Western New York Study

Objective: To examine whether several biomarkers of endothelial function and inflammation improve prediction of type 2 diabetes over 5.9 years of follow‐up, independent of traditional risk factors. Methods and Procedures: A total of 1,455 participants from the Western New York Study, free of type 2 diabetes at baseline, were selected. Incident type 2 diabetes was defined as fasting glucose exceeding 125 mg/dl or on antidiabetic medication at the follow‐up visit. Sixty‐one people who met the case definition (8/1,000 person years) were identified and individually matched with up to three controls on gender, race, year of study enrollment, and baseline fasting glucose (<110 or 110–125 mg/dl). Biomarkers were measured from frozen baseline samples. Results: In conditional logistic regression analyses accounting for traditional risk factors (age, family history of diabetes, smoking, drinking status, and BMI), E‐selectin was positively related (3rd vs. 1st tertile: odds ratio 2.77, 95% confidence interval (CI) 1.13–6.79, P for linear trend = 0.023) and serum albumin was inversely related (3rd vs. 1st tertile: odds ratio 0.36, 95% CI 0.14–0.93, P for linear trend = 0.032) to type 2 diabetes incidence. The addition of E‐selectin, serum albumin, and leukocyte count to a basic risk factor model including only traditional risk factors significantly increased the area under the receiver operating characteristic curve (AUC) (from 0.646 to 0.726, P value = 0.04). Discussion: These results support the role of endothelial dysfunction and subclinical inflammation as important mechanisms in the etiopathogenesis of type 2 diabetes; moreover, they indicate that novel biomarkers may improve the prediction of type 2 diabetes beyond the use of traditional risk factors alone.