Zur Bestimmung der verdaulichen Stickstoffsubstanz und des Eiweisstickstoffs in Futter- und Nahrungsmitteln

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Influence of antibiotic pressure on bacterial bioluminescence, with emphasis on Staphylococcus aureus

Bioluminescence imaging is used for longitudinal evaluation of bacteria in live animals. Clear relations exist between bacterial numbers and their bioluminescence. However, bioluminescence images of Staphylococcus aureus Xen29, S. aureus Xen36 and Escherichia coli Xen14 grown on tryptone soy agar in Etests demonstrated increased bioluminescence at sub-MICs of different antibiotics. This study aimed to further evaluate the influence of antibiotic pressure on bioluminescence in S. aureus Xen29. Bioluminescence of S. aureus Xen29, grown planktonically in tryptone soy broth, was quantified in the absence and presence of different concentrations of vancomycin, ciprofloxacin, erythromycin or chloramphenicol and was related to expression of the luxA gene under antibiotic pressure measured using real-time PCR. In the absence of antibiotics, staphylococcal bioluminescence increased over time until a maximum after ca. 6 h of growth, and subsequently decreased to the detection threshold after 24 h of growth owing to reduced bacterial metabolic activity. Up to MICs of the antibiotics, bioluminescence increased according to a similar pattern up to 6 h of growth, but after 24 h bioluminescence was higher than in the absence of antibiotics. Contrary to expectations, bioluminescence per organism (CFU) after different growth periods in the absence and at MICs of different antibiotics decreased with increasing expression of luxA. Summarising, antibiotic pressure impacts the relation between CFU and bioluminescence. Under antibiotic pressure, bioluminescence is not controlled by luxA expression but by co-factors impacting the bacterial metabolic activity. This conclusion is of utmost importance when evaluating antibiotic efficacy in live animals using bioluminescent bacterial strains. (C) 2015 Elsevier B.V. and the International Society of Chemotherapy. All rights reserved

Massively parallel sequencing of the mouse exome to accurately identify rare, induced mutations: an immediate source for thousands of new mouse models

Accurate identification of sparse heterozygous single-nucleotide variants (SNVs) is a critical challenge for identifying the causative mutations in mouse genetic screens, human genetic diseases and cancer. When seeking to identify causal DNA variants that occur at such low rates, they are overwhelmed by false-positive calls that arise from a range of technical and biological sources. We describe a strategy using whole-exome capture, massively parallel DNA sequencing and computational analysis, which identifies with a low false-positive rate the majority of heterozygous and homozygous SNVs arising de novo with a frequency of one nucleotide substitution per megabase in progeny of N-ethyl-N-nitrosourea (ENU)-mutated C57BL/6j mice. We found that by applying a strategy of filtering raw SNV calls against known and platform-specific variants we could call true SNVs with a false-positive rate of 19.4 per cent and an estimated false-negative rate of 21.3 per cent. These error rates are small enough to enable calling a causative mutation from both homozygous and heterozygous candidate mutation lists with little or no further experimental validation. The efficacy of this approach is demonstrated by identifying the causative mutation in the Ptprc gene in a lymphocyte-deficient strain and in 11 other strains with immune disorders or obesity, without the need for meiotic mapping. Exome sequencing of first-generation mutant mice revealed hundreds of unphenotyped protein-changing mutations, 52 per cent of which are predicted to be deleterious, which now become available for breeding and experimental analysis. We show that exome sequencing data alone are sufficient to identify induced mutations. This approach transforms genetic screens in mice, establishes a general strategy for analysing rare DNA variants and opens up a large new source for experimental models of human disease

Nachweis und Bestimmung der Halogensauerstoffverbindungen

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