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.     

Lipidic phase membrane protein serial femtosecond crystallography

X-ray free electron laser (X-FEL)-based serial femtosecond crystallography is an emerging method with potential to rapidly advance the challenging field of membrane protein structural biology. Here we recorded interpretable diffraction data from micrometer-sized lipidic sponge phase crystals of the Blastochloris viridis photosynthetic reaction center delivered into an X-FEL beam using a sponge phase micro-jet.     

Meta-analysis of genome-wide scans for total body BMD in children and adults reveals allelic heterogeneity and age-specific effects at the WNT16 locus

To identify genetic loci influencing bone accrual, we performed a genome-wide association scan for total-body bone mineral density (TB-BMD) variation in 2,660 children of different ethnicities. We discovered variants in 7q31.31 associated with BMD measurements, with the lowest P = 4.1 × 10(-11) observed for rs917727 with minor allele frequency of 0.37. We sought replication for all SNPs located ± 500 kb from rs917727 in 11,052 additional individuals from five independent studies including children and adults, together with de novo genotyping of rs3801387 (in perfect linkage disequilibrium (LD) with rs917727) in 1,014 mothers of children from the discovery cohort. The top signal mapping in the surroundings of WNT16 was replicated across studies with a meta-analysis P = 2.6 × 10(-31) and an effect size explaining between 0.6%-1.8% of TB-BMD variance. Conditional analyses on this signal revealed a secondary signal for total body BMD (P = 1.42 × 10(-10)) for rs4609139 and mapping to C7orf58. We also examined the genomic region for association with skull BMD to test if the associations were independent of skeletal loading. We identified two signals influencing skull BMD variation, including rs917727 (P = 1.9 × 10(-16)) and rs7801723 (P = 8.9 × 10(-28)), also mapping to C7orf58 (r(2) = 0.50 with rs4609139). Wnt16 knockout (KO) mice with reduced total body BMD and gene expression profiles in human bone biopsies support a role of C7orf58 and WNT16 on the BMD phenotypes observed at the human population level. In summary, we detected two independent signals influencing total body and skull BMD variation in children and adults, thus demonstrating the presence of allelic heterogeneity at the WNT16 locus. One of the skull BMD signals mapping to C7orf58 is mostly driven by children, suggesting temporal determination on peak bone mass acquisition. Our life-course approach postulates that these genetic effects influencing peak bone mass accrual may impact the risk of osteoporosis later in life.     

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.     

Effects of Inoculum Additions in the Presence of a Preestablished Arbuscular Mycorrhizal Fungal Community

Communities of arbuscular mycorrhizal fungi (AMF) are crucial for promoting plant productivity in most terrestrial systems, including anthropogenically managed ecosystems. Application of AMF inocula has therefore become a widespread practice. It is, however, pertinent to understand the mechanisms that govern AMF community composition and their performance in order to design successful manipulations. Here we assess whether the composition and plant growth-promotional effects of a synthetic AMF community can be altered by inoculum additions of the isolates forming the community. This was determined by following the effects of three AMF isolates, each inoculated in two propagule densities into a preestablished AMF community. Fungal abundance in roots and plant growth were evaluated in three sequential harvests. We found a transient positive response in AMF abundance to the intraspecific inoculation only in the competitively weakest isolate. The other two isolates responded negatively to intra- and interspecific inoculations, and in some cases plant growth was also reduced. Our results suggest that increasing the AMF density may lead to increased competition among fungi and a trade-off with their ability to promote plant productivity. This is a key ecological aspect to consider when introducing AMF into soils.