Modellprojekt zur Verknüpfung von Arbeits- und Gesundheitsförderung im Setting

MODELLPROJEKT ZUR VERKNÜPFUNG VON ARBEITS- UND GESUNDHEITSFÖRDERUNG IM SETTING Modellprojekt zur Verknüpfung von Arbeits- und Gesundheitsförderung im Setting / Schreiner-Kürten, Karin (Rights reserved) ( -

Genotyping-by-sequencing-based identification of Arabidopsis pattern recognition receptor RLP32 recognizing proteobacterial translation initiation factor IF1

Activation of plant pattern-triggered immunity (PTI) relies on the recognition of microbe-derived structures, termed patterns, through plant-encoded surface-resident pattern recognition receptors (PRRs). We show that proteobacterial translation initiation factor 1 (IF1) triggers PTI in Arabidopsis thaliana and related Brassicaceae species. Unlike for most other immunogenic patterns, IF1 elicitor activity cannot be assigned to a small peptide epitope, suggesting that tertiary fold features are required for IF1 receptor activation. We have deployed natural variation in IF1 sensitivity to identify Arabidopsis leucine-rich repeat (LRR) receptor-like protein 32 (RLP32) as IF1 receptor using a restriction site-associated DNA sequencing approach. RLP32 confers IF1 sensitivity to rlp32 mutants, IF1-insensitive Arabidopsis accessions and IF1-insensitive Nicotiana benthamiana, binds IF1 specifically and forms complexes with LRR receptor kinases SOBIR1 and BAK1 to mediate signaling. Similar to other PRRs, RLP32 confers resistance to Pseudomonas syringae, highlighting an unexpectedly complex array of bacterial pattern sensors within a single plant species

Genotyping-by-sequencing-based identification of Arabidopsis pattern recognition receptor RLP32 recognizing proteobacterial translation initiation factor IF1

Activation of plant pattern-triggered immunity (PTI) relies on the recognition of microbe-derived structures, termed patterns, through plant-encoded surface-resident pattern recognition receptors (PRRs). We show that proteobacterial translation initiation factor 1 (IF1) triggers PTI in Arabidopsis thaliana and related Brassicaceae species. Unlike for most other immunogenic patterns, IF1 elicitor activity cannot be assigned to a small peptide epitope, suggesting that tertiary fold features are required for IF1 receptor activation. We have deployed natural variation in IF1 sensitivity to identify Arabidopsis leucine-rich repeat (LRR) receptor-like protein 32 (RLP32) as IF1 receptor using a restriction site-associated DNA sequencing approach. RLP32 confers IF1 sensitivity to rlp32 mutants, IF1-insensitive Arabidopsis accessions and IF1-insensitive Nicotiana benthamiana, binds IF1 specifically and forms complexes with LRR receptor kinases SOBIR1 and BAK1 to mediate signaling. Similar to other PRRs, RLP32 confers resistance to Pseudomonas syringae, highlighting an unexpectedly complex array of bacterial pattern sensors within a single plant species

Correlations between milk and plasma levels of amino and carboxylic acids in dairy cows.

The objective of this study was to investigate the relationship between the concentrations of 19 amino acids, glucose, and seven carboxylic acids in the blood and milk of dairy cows and their correlations with established markers of ketosis. To that end, blood plasma and milk specimens were collected throughout lactation in two breeds of dairy cows of different milk yield. Plasma concentrations of glucose, pyruvate, lactate, α-aminobutyrate, β-hydroxybutyrate (BHBA), and most amino acids, except for glutamate and aspartate, were on average 9.9-fold higher than their respective milk levels. In contrast, glutamate, aspartate, and the Krebs cycle intermediates succinate, fumarate, malate, and citrate were on average 9.1-fold higher in milk than in plasma. For most metabolites, with the exception of BHBA and threonine, no significant correlations were observed between their levels in plasma and milk. Additionally, milk levels of acetone showed significant direct relationships with the glycine-to-alanine ratio and the BHBA concentration in plasma. The marked decline in plasma concentrations of glucose, pyruvate, lactate, and alanine in cows with plasma BHBA levels above the diagnostic cutoff point for subclinical ketosis suggests that these animals fail to meet their glucose demand and, as a consequence, rely increasingly on ketone bodies as a source of energy. The concomitant increase in plasma glycine may reflect not only the excessive depletion of protein reserves but also a potential deficiency of vitamin B6

Metabolite extraction from adherently growing mammalian cells for metabolomics studies: optimization of harvesting and extraction protocols

Trypsin/ethylenediaminetetraacetic acid (EDTA) treatment and cell scraping in a buffer solution were compared for harvesting adherently growing mammalian SW480 cells for metabolomics studies. In addition, direct scraping with a solvent was tested. Trypsinated and scraped cell pellets were extracted using seven different extraction protocols including pure methanol, methanol/water, pure acetone, acetone/water, methanol/chloroform/water, methanol/isopropanol/water, and acid-base methanol. The extracts were analyzed by GC-MS after methoximation/silylation and derivatization with propyl chloroformate, respectively. The metabolic fingerprints were compared and 25 selected metabolites including amino acids and intermediates of energy metabolism were quantitatively determined. Moreover, the influence of freeze/thaw cycles, ultrasonication and homogenization using ceramic beads on extraction yield was tested. Pure acetone yielded the lowest extraction efficiency while methanol, methanol/water, methanol/isopropanol/water, and acid-base methanol recovered similar metabolite amounts with good reproducibility. Based on overall performance, methanol/water was chosen as a suitable extraction solvent. Repeated freeze/thaw cycles, ultrasonication and homogenization did not improve overall metabolite yield of the methanol/water extraction. Trypsin/EDTA treatment caused substantial metabolite leakage proving it inadequate for metabolomics studies. Gentle scraping of the cells in a buffer solution and subsequent extraction with methanol/water resulted on average in a sevenfold lower recovery of quantified metabolites compared with direct scraping using methanol/water, making the latter one the method of choice to harvest and extract metabolites from adherently growing mammalian SW480 cells

Improved enantiomer resolution and quantification of free D-amino acids in serum and urine by comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry

The potential of comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC×GC-TOFMS) in the quantitative analysis of amino acid enantiomers (AAEs) as their methyl chloroformate (MCF) derivatives in physiological fluids was investigated. Of the two column sets tested, the combination of an Rt-γDEXsa chiral column with a polar ZB-AAA column provided superior selectivity. Twenty AAEs were baseline resolved including L-Leu and D-Ile, which had failed separation by one-dimensional chiral GC-quadrupole-MS (GC-qMS). Lower limits of quantification (LLOQ) were in the range of 0.03-2 μM. Reproducibility of the analysis of a serum specimen in octaplicate ranged from 1.3 to 16.6%. The GC×GC-TOFMS method was validated by analyzing AAEs in 48 urine and 43 serum specimens, respectively, and by comparing the results with data obtained by a previously validated GC-qMS method. Mean recoveries ranged from 78.4% for D-Leu to 116.4% for D-Pro in urine and 72.2% for L-Thr to 129.4% for L-Ile in serum. The method was applied to the comparison of AAE serum levels in patients suffering from liver cirrhosis to a control group. Significantly increased D-AA concentrations were found for the patient group, whereas L-AA levels were slightly decreased

Performance evaluation of gas chromatography-atmospheric pressure chemical ionization-time-of-flight mass spectrometry for metabolic fingerprinting and profiling

Gas chromatography-atmospheric-pressure chemical ionization-time-of-flight mass spectrometry (GC-APCI-TOFMS) was compared to GC × GC-electron ionization (EI)-TOFMS, GC-EI-TOFMS, GC-chemical ionization (CI)-quadrupole mass spectrometry (qMS), and GC-EI-qMS in terms of reproducibility, dynamic range, limit of detection, and quantification using a mix of 43 metabolites and 12 stable isotope-labeled standards. Lower limits of quantification for GC-APCI-TOFMS ranged between 0.06 and 7.81 μM, and relative standard deviations for calibration replicates were between 0.4% and 8.7%. For all compounds and techniques, except in four cases, R(2) values were above 0.99. Regarding limits of quantification, GC-APCI-TOFMS was inferior to only GC × GC-EI-TOFMS, but outperformed all other techniques tested. GC-APCI-TOFMS was further applied to the metabolic fingerprinting of two Escherichia coli strains. Of 45 features that differed significantly (false discovery rate < 0.05) between the strains, 25 metabolites were identified through highly accurate and reproducible (Δm ± SD below 5 mDa over m/z 190-722) mass measurements. Starting from the quasimolecular ion, six additional metabolites were identified that had not been found in a previous study using GC × GC-EI-TOFMS and an EI mass spectral library for identification purposes. Silylation adducts formed in the APCI source assisted the identification of unknown compounds, as their formation is structure-dependent and is not observed for compounds lacking a carboxylic group