Synthetic post-translational modifications of elongation factor P using the ligase EpmA

Canonically, tRNA synthetases charge tRNA. However, the lysyl-tRNA synthetase paralog EpmA catalyzes the attachment of (R)-beta-lysine to the epsilon-amino group of lysine 34 of the translation elongation factor P (EF-P) inEscherichia coli. This modification is essential for EF-P-mediated translational rescue of ribosomes stalled at consecutive prolines. In this study, we determined the kinetics of EpmA and its variant EpmA_A298G to catalyze the post-translational modification of K34 in EF-P with eight noncanonical substrates. In addition, acetylated EF-P was generated using an amber suppression system. The impact of these synthetically modified EF-P variants onin vitrotranslation of a polyproline-containing NanoLuc luciferase reporter was analyzed. Our results show that natural (R)-beta-lysylation was more effective in rescuing stalled ribosomes than any other synthetic modification tested. Thus, our work not only provides new biochemical insights into the function of EF-P, but also opens a new route to post-translationally modify proteins using EpmA

Pflanzen für die Gesundheit-Vorstellung eines neuen interdisziplinären Forschungsprojektes zum ökologischen Anbau von Arzneipflanzen

Ecologically grown medicinal plants containing bioactive compounds hold great poten-tial as high-value niche crops for farmers. However, the way to grow these plants differs from traditional crops. Growing techniques, harvest methods and postharvest handling of the raw material plays a crucial role regarding the quality of the raw material that the farmers can offer. The purpose of a new research project financed by EU-Interreg IIIA programme is among other things to carry out production, harvest and processing experiments with plants containing bioactive plant compounds that hold a preventive effect toward diabetes II. One of the project´s goals is to draw up cultivation instructions for the primary producers to use when cultivating the plants in question. Examples of the plants that are being examined in the project are Goat´s Rue (Galega officinalis) and Fenugreek (Trigonella foenum-graecum)

Switching the Post-translational Modification of Translation Elongation Factor EF-P

Tripeptides with two consecutive prolines are the shortest and most frequent sequences causing ribosome stalling. The bacterial translation elongation factor P (EF-P) relieves this arrest, allowing protein biosynthesis to continue. A seven amino acids long loop between beta-strands β3/β4 is crucial for EF-P function and modified at its tip by lysylation of lysine or rhamnosylation of arginine. Phylogenetic analyses unveiled an invariant proline in the -2 position of the modification site in EF-Ps that utilize lysine modifications such as Escherichia coli. Bacteria with the arginine modification like Pseudomonas putida on the contrary have selected against it. Focusing on the EF- Ps from these two model organisms we demonstrate the importance of the β3/β4 loop composition for functionalization by chemically distinct modifications. Ultimately, we show that only two amino acid changes in E. coli EF-P are needed for switching the modification strategy from lysylation to rhamnosylation

A New Method for Investigation of the Hair Shaft: Hard X-Ray Microscopy with a 90-nm Spatial Resolution

Various methods have been used to investigate the hair shaft. In the ultrastructural hair field, scanning and transmission electron microscopies are widely used investigative methods, but they have some technical limitations. Recently, X-ray microscopes with sub-micron spatial resolution have emerged as useful instruments because they offer a unique opportunity to observe the interior of an undamaged sample in greater detail. In this report, we examined damaged hair shaft tips using hard X-ray microscopy with a 90 nm spatial resolution. The results of this study suggest that hard X-ray microscopy is an alternative investigative method for hair morphology studies

Comparative analysis of prototype two-component systems with either bifunctional or monofunctional sensors: differences in molecular structure and physiological function

Signal transduction by a traditional two-component system involves a sensor protein that recognizes a physiological signal, autophosphorylates and transfers its phosphate, and a response regulator protein that receives the phosphate, alters its affinity toward specific target proteins or DNA sequences and causes change in metabolic activity or gene expression. In some cases the sensor protein, when unphosphorylated, has a positive effect upon the rate of dephosphorylation of the regulator protein (bifunctional sensor), whereas in other cases it has no such effect (monofunctional sensor). In this work we identify structural and functional differences between these two designs. In the first part of the paper we use sequence data for two-component systems from several organisms and homology modelling techniques to determine structural features for response regulators and for sensors. Our results indicate that each type of reference sensor (bifunctional and monofunctional) has a distinctive structural feature, which we use to make predictions regarding the functionality of other sensors. In the second part of the paper we use mathematical models to analyse and compare the physiological function of systems that differ in the type of sensor and are otherwise equivalent. Our results show that a bifunctional sensor is better than a monofunctional sensor both at amplifying changes in the phosphorylation level of the regulator caused by signals from the sensor and at attenuating changes caused by signals from small phosphodonors. Cross-talk to or from other two-component systems is better suppressed if the transmitting sensor is monofunctional, which is the more appropriate design when such cross-talk represents pathological noise. Cross-talk to or from other two-component systems is better amplified if the transmitting sensor is bifunctional, which is the more appropriate design when such cross-talk represents a physiological signal. These results provide a functional rationale for the selection of each design that is consistent with available experimental evidence for several two-component systems.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74871/1/j.1365-2958.2003.03344.x.pd

The anti-obesity effect of Lethariella cladonioides in 3T3-L1 cells and obese mice

The aim of this study was to investigate whether a water extract of L. cladonioides (LC) has an anti-obesity effect in 3T3-L1 cells and obese mice. Treatment of differentiated 3T3-L1 adipocytes with LC caused a significant increase in glycerol release and reduced the protein expression of the adipogenic transcription factors, PPARγ and C/EBPα. In an animal model, obese mice were artificially induced by a high fat diet for 10 weeks. Experimental groups were treated with LC (100 mg/kg/day) by gavage for the next 10 weeks. At the end of experiment, the body weight of the LC group mice was reduced by 14.2% compared to the high fat diet (HFD) group. The treatment also decreased liver (31.0%), epididymal (18.0%) and retroperitoneal (19.3%) adipose tissue, and kidney (6.7%) weights, respectively, compared with those of the HFD group. LC prevented diet-induced increases in the serum level of TC (22.6%), TG (11.6%), and glucose (35.0%), respectively, compared with the HFD group. However, the HDL-C level was higher in the LC group (26.1%) than the HFD group. The results of this study thus suggest that LC suppressed lipid accumulation and expression of adipogenic transcription factors, and increased the amount of glycerol release. LC also indicated an anti-obese and anti-hyperlipidemic effect

The Role of the p38 MAPK Signaling Pathway in High Glucose-Induced Epithelial-Mesenchymal Transition of Cultured Human Renal Tubular Epithelial Cells

Epithelial-mesenchymal transition of tubular epithelial cells, which is characterized by a loss of epithelial cell characteristics and a gain of ECM-producing myofibroblast characteristics, is an essential mechanism that is involved in tubulointerstitial fibrosis, an important component of the renal injury that is associated with diabetic nephropathy. Under diabetic conditions, p38 MAPK activation has been reported in glomeruli and mesangial cells; however, studies on p38 MAPK in TECs are lacking. In this study, the role of p38 MAPK in AP-1 activation and in the EMT in the human proximal tubular epithelial cell line (HK-2) under high glucose concentration conditions is investigated.A vector for small interfering RNA that targets p38 MAPK was constructed; the cells were then either transfected with p38 siRNA or pretreated with a chemical inhibitor of AP-1 and incubated with low glucose plus TGF-β1 or high glucose for 48 h. Cells that were not transfected or pretreated and were exposed to low glucose with or without TGF-β1 or high glucose for 48 h were considered to be the controls. We found that high glucose induced an increase in TGF-β1. And high glucose-induced p38 MAPK activation was inhibited by p38 siRNA (P<0.05). A significant decline in E-cadherin and CK expression and a notable increase in vimentin and α-SMA were detected when exposed to low glucose with TGF-β1 or high glucose, and a significant raise of secreted fibronectin were detected when exposed to high glucose; whereas these changes were reversed when the cells were treated with p38 siRNA or AP-1 inhibitor (P<0.05). AP-1 activity levels and Snail expression were up-regulated under high glucose conditions but were markedly down-regulated through knockdown of p38 MAPK with p38 siRNA or pretreatment with AP-1 inhibitor (P<0.05).This study suggests that p38 MAPK may play an important role in the high glucose-induced EMT by activating AP-1 in tubular epithelial cells

Reconstruction of cellular variability from spatiotemporal patterns of Dictyostelium discoideum

Variability in cell properties can be an important driving mechanism behind spatiotemporal patterns in biological systems, as the degree of cell-to-cell differences determines the capacity of cells to locally synchronize and, consequently, form patterns on a larger spatial scale. In principle, certain features of spatial patterns emerging with time may be regulated by variability or, more specifically, by certain constellations of cell-to-cell differences. Similarly, measuring variability in a system (i.e. the spatial distribution of cell-cell differences) may help predict properties of later-stage patterns

State-of-the art data normalization methods improve NMR-based metabolomic analysis

Extracting biomedical information from large metabolomic datasets by multivariate data analysis is of considerable complexity. Common challenges include among others screening for differentially produced metabolites, estimation of fold changes, and sample classification. Prior to these analysis steps, it is important to minimize contributions from unwanted biases and experimental variance. This is the goal of data preprocessing. In this work, different data normalization methods were compared systematically employing two different datasets generated by means of nuclear magnetic resonance (NMR) spectroscopy. To this end, two different types of normalization methods were used, one aiming to remove unwanted sample-to-sample variation while the other adjusts the variance of the different metabolites by variable scaling and variance stabilization methods. The impact of all methods tested on sample classification was evaluated on urinary NMR fingerprints obtained from healthy volunteers and patients suffering from autosomal polycystic kidney disease (ADPKD). Performance in terms of screening for differentially produced metabolites was investigated on a dataset following a Latin-square design, where varied amounts of 8 different metabolites were spiked into a human urine matrix while keeping the total spike-in amount constant. In addition, specific tests were conducted to systematically investigate the influence of the different preprocessing methods on the structure of the analyzed data. In conclusion, preprocessing methods originally developed for DNA microarray analysis, in particular, Quantile and Cubic-Spline Normalization, performed best in reducing bias, accurately detecting fold changes, and classifying samples