Identification of a pKa-regulating motif stabilizing imidazole-modified double-stranded DNA.

The predictable 3D structure of double-stranded DNA renders it ideally suited as a template for the bottom-up design of functionalized nucleic acid-based active sites. We here explore the use of a 14mer DNA duplex as a scaffold for the precise and predictable positioning of catalytic functionalities. Given the ubiquitous participation of the histidine-based imidazole group in protein recognition and catalysis events, single histidine-like modified duplexes were investigated. Tethering histamine to the C5 of the thymine base via an amide bond, allows the flexible positioning of the imidazole function in the major groove. The mutual interactions between the imidazole and the duplex and its influence on the imidazolium pKaH are investigated by placing a single modified thymine at four different positions in the center of the 14mer double helix. Using NMR and unrestrained molecular dynamics, a structural motif involving the formation of a hydrogen bond between the imidazole and the Hoogsteen side of the guanine bases of two neighboring GC base pairs is established. The motif contributes to a stabilization against thermal melting of 6°C and is key in modulating the pKaH of the imidazolium group. The general features, prerequisites and generic character of the new pKaH-regulating motif are described.

Quantitative contrasts in the photopolymerization of acrylamide and methacrylamide-functionalized gelatin hydrogel building blocks.

The synthesis and evaluation of gelatin acrylamide as an alternative to the well-established gelatin methacrylamide are reported. High-resolution magic angle spinning NMR is used for the quantitative determination of the chemical cross-linking density. The gelatin acrylamide precursors reveal enhanced cross-linking in terms of reactivity and double bond conversion, resulting in stronger networks. Remarkably, even at very low double bond conversions, ≈5%, gel fractions of ≈40% are obtained. The cross-linked networks are also reviewed in the framework of the rubber elasticity and thermodynamic swelling theories to estimate important nanostructural properties. Preliminary cell tests revealed that highly viable (>90%) cell-laden constructs are obtained.

(1)H NMR based metabolomics of CSF and blood serum: a metabolic profile for a transgenic rat model of Huntington disease.

Huntington disease (HD) is a hereditary brain disease. Although the causative gene has been found, the exact mechanisms of the pathogenesis are still unknown. Recent investigations point to metabolic and energetic dysfunctions in HD neurons. Both univariate and multivariate analyses were used to compare proton nuclear magnetic resonance spectra of serum and cerebrospinal fluid (CSF) taken from presymptomatic HD transgenic rats and their wild-type littermates. N-acetylaspartate (NAA), was found to be significantly decreased in the serum of HD rats compared to wild-type littermates. Moreover, in the serum their levels of glutamine, succinic acid, glucose and lactate are significantly increased as well. An increased concentration of lactate and glucose is also found in CSF. There is a 1:1 stoichiometry coupling glucose utilization and glutamate cycling. The observed increase in the glutamine concentration, which indicates a shutdown in the neuronal-glial glutamate-glutamine cycling, results therefore in an increased glucose concentration. The elevated succinic acid concentration might be due to an inhibition of succinate dehydrogenase, an enzyme linked to the mitochondrial respiratory chain and TCA cycle. Moreover, reduced levels of NAA may reflect an impairment of mitochondrial energy production. In addition, the observed difference in lactate supports a deficiency of oxidative energy metabolism in rats transgenic for HD as well. The observed metabolic alterations seem to be more profound in serum than in CSF in presymptomatic rats. All findings suggest that even in presymptomatic rats, a defect in energy metabolism is already apparent. These results support the hypothesis of mitochondrial energy dysfunction in HD.

Evaluation of standard and advanced preprocessing methods for the univariate analysis of blood serum 1H-NMR spectra.

Proton nuclear magnetic resonance ((1)H-NMR)-based metabolomics enables the high-resolution and high-throughput assessment of a broad spectrum of metabolites in biofluids. Despite the straightforward character of the experimental methodology, the analysis of spectral profiles is rather complex, particularly due to the requirement of numerous data preprocessing steps. Here, we evaluate how several of the most common preprocessing procedures affect the subsequent univariate analyses of blood serum spectra, with a particular focus on how the standard methods perform compared to more advanced examples. Carr-Purcell-Meiboom-Gill 1D (1)H spectra were obtained for 240 serum samples from healthy subjects of the Asklepios study. We studied the impact of different preprocessing steps--integral (standard method) and probabilistic quotient normalization; no, equidistant (standard), and adaptive-intelligent binning; mean (standard) and maximum bin intensity data summation--on the resonance intensities of three different types of metabolites: triglycerides, glucose, and creatinine. The effects were evaluated by correlating the differently preprocessed NMR data with the independently measured metabolite concentrations. The analyses revealed that the standard methods performed inferiorly and that a combination of probabilistic quotient normalization after adaptive-intelligent binning and maximum intensity variable definition yielded the best overall results (triglycerides, R = 0.98; glucose, R = 0.76; creatinine, R = 0.70). Therefore, at least in the case of serum metabolomics, these or equivalent methods should be preferred above the standard preprocessing methods, particularly for univariate analyses. Additional optimization of the normalization procedure might further improve the analyses.

NMR-based characterization of metabolic alterations in hypertension using an adaptive, intelligent binning algorithm.

As with every -omics technology, metabolomics requires new methodologies for data processing. Due to the large spectral size, a standard approach in NMR-based metabolomics implies the division of spectra into equally sized bins, thereby simplifying subsequent data analysis. Yet, disadvantages are the loss of information and the occurrence of artifacts caused by peak shifts. Here, a new binning algorithm, Adaptive Intelligent Binning (AI-Binning), which largely circumvents these problems, is presented. AI-Binning recursively identifies bin edges in existing bins, requires only minimal user input, and avoids the use of arbitrary parameters or reference spectra. The performance of AI-Binning is demonstrated using serum spectra from 40 hypertensive and 40 matched normotensive subjects from the Asklepios study. Hypertension is a major cardiovascular risk factor characterized by a complex biochemistry and, in most cases, an unknown origin. The binning algorithm resulted in an improved classification of hypertensive status compared with that of standard binning and facilitated the identification of relevant metabolites. Moreover, since the occurrence of noise variables is largely avoided, AI-Binned spectra can be unit-variance scaled. This enables the detection of relevant, low-intensity metabolites. These results demonstrate the power of AI-Binning and suggest the involvement of alpha-1 acid glycoproteins and choline biochemistry in hypertension.

Insights into electrolytic stabilization with weak polarization as treatment for archaeological copper objects.

Immersion of corroded copper artefacts in dilute sodium sesquicarbonate solution is a well-recognized stabilization technique--especially in the conservation of objects recovered from marine environments and therefore saturated with chlorides. Here we describe three linked experiments performed to investigate a variation on this treatment, involving the application of a low potential to the artefact in order to drive the chloride extraction process. This includes a new spectroelectrochemical approach which allows 2-D pseudorandom X-ray reflection diffraction patterns to be obtained without interrupting the reaction in solution. Experiments were carried out on synthetically produced chloride layers on copper (nantokite and atacamite). We show that a thick chloride layer is, in general, replaced by a thin cuprite layer through a mechanism which involves detachment of the chloride crystallites from the surface prior to dissolution.