Zur Taxonomie von Rhodopseudomonas palustris

Zusammenfassung Eine Reihe von Rhodopseudomonas palustris-Stämmen aus verschiedenen Herkünften wurden vergleichend unter Verwendung folgender Merkmale untersucht: Substratverwertung, in vivo-Absorptionsspektrum und Serologie der O-Antigene. Die gegen 2 Stämme gerichteten Antiseren zeigen hohe Spezifität. Die Verwendbarkeit der serologischen Kreuzreaktion für taxonomische Untersuchungen bei photosynthetischen Bakterien wird diskutiert.

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On the taxonomy of Rhodopseudomonas palustris

Summary Strains of Rhodopseudomonas palustris isolated from different habitats were compared with respect to their taxonomic features. All strains grew very well on formiate, acetate, propionate, butyrate, aspartate, inositol, ethanol, fructose, and p-amino-benzoate, respectively, as single carbon source. Most of the strains were able to use benzoic acid or glucose, too. But alanine was not found to be a good substrate. The maxima of the bacteriochlorophyll in-vivo-absorption spectra were estimated to be 376, 589, 802–805, and 858–875 nm. The shift of the infrared peak in the different strains is loosely correlated with the change of the carotenoid in vivo spectrum, the maxima of which were measured to be 470–480 nm (shoulder) 495–505 nm, and 520–545 nm (shoulder). Antisera were prepared against the strains 1e5 and 11/1. It was demonstrated that these antisera were directed against the lipopolysaccharides (O-antigen) of these bacteria. The antigen of 1e5 does not cross react with the antigen of 11/1. Strain 1e5 is the only one of 17 strains tested which is sensitive to the bacteriophage Rp1. The antigen of this strain cross reacted only with the antigen of strain K1. In contrast, the antigen of strain 11/1 cross reacted in some degree with most of the tested strains of Rps. palustris. No or very weak cross reaction was observed between the antigens of Rps. palustris (1e5, 11/1) and Rps. capsulata, Rps. spheroides, or R. rubrum, respectively. In contrast to 11/1 only heat-killed cells of strain 1e5 were agglutinated by anti-1e5.

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Im Text verwendete Abkürzungen LPS Lipopolysaccharid - R Rhodospirillum - Rps. Rhodopseudomonas - i.m. intramuskulär - s.c. subcutan - i.v. intravenös     

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.

     

Plasma Biomarkers Discriminate Clinical Forms of Multiple Sclerosis

Multiple sclerosis, the most common cause of neurological disability in young population after trauma, represents a significant public health burden. Current challenges associated with management of multiple sclerosis (MS) patients stem from the lack of biomarkers that might enable stratification of the different clinical forms of MS and thus prompt treatment for those patients with progressive MS, for whom there is currently no therapy available. In the present work we analyzed a set of thirty different plasma cytokines, chemokines and growth factors present in circulation of 129 MS patients with different clinical forms (relapsing remitting, secondary progressive and primary progressive MS) and 53 healthy controls, across two independent cohorts. The set of plasma analytes was quantified with Luminex xMAP technology and their predictive power regarding clinical outcome was evaluated both individually using ROC curves and in combination using logistic regression analysis. Our results from two independent cohorts of MS patients demonstrate that the divergent clinical and histology-based MS forms are associated with distinct profiles of circulating plasma protein biomarkers, with distinct signatures being composed of chemokines and growth/angiogenic factors. With this work, we propose that an evaluation of a set of 4 circulating biomarkers (HGF, Eotaxin/CCL11, EGF and MIP-1β/CCL4) in MS patients might serve as an effective tool in the diagnosis and more personalized therapeutic targeting of MS patients.