No genetic footprints of the fat mass and obesity associated (FTO) gene in human plasma 1H CPMG NMR metabolic profiles

In this paper it was investigated if any genotypic footprints from the fat mass and obesity associated (FTO) SNP could be found in 600 MHz ¹H CPMG NMR profiles of around 1,000 human plasma samples from healthy Danish twins. The problem was addressed with a combination of univariate and multivariate methods. The NMR data was substantially compressed using principal component analysis or multivariate curve resolution-alternating least squares with focus on chemically meaningful feature selection reflecting the nature of chemical signals in an NMR spectrum. The possible existence of an FTO signature in the plasma samples was investigated at the subject level using supervised multivariate classification in the form of extended canonical variate analysis, classification tree modeling and Lasso (L1) regularized linear logistic regression model (GLMNET). Univariate hypothesis testing of peak intensities was used to explore the genotypic effect on the plasma at the population level. The multivariate classification approaches indicated poor discriminative power of the metabolic profiles whereas univariate hypothesis testing provided seven spectral regions with p < 0.05. Applying false discovery rate control, no reliable markers could be identified, which was confirmed by test set validation. We conclude that it is very unlikely that an FTO-correlated signal can be identified in these ¹H CPMG NMR plasma metabolic profiles and speculate that high-throughput un-targeted genotype-metabolic correlations will in many cases be a difficult path to follow.     

Probiotic modulation of symbiotic gut microbial–host metabolic interactions in a humanized microbiome mouse model

The transgenomic metabolic effects of exposure to either Lactobacillus paracasei or Lactobacillus rhamnosus probiotics have been measured and mapped in humanized extended genome mice (germ‐free mice colonized with human baby flora). Statistical analysis of the compartmental fluctuations in diverse metabolic compartments, including biofluids, tissue and cecal short‐chain fatty acids (SCFAs) in relation to microbial population modulation generated a novel top‐down systems biology view of the host response to probiotic intervention. Probiotic exposure exerted microbiome modification and resulted in altered hepatic lipid metabolism coupled with lowered plasma lipoprotein levels and apparent stimulated glycolysis. Probiotic treatments also altered a diverse range of pathways outcomes, including amino‐acid metabolism, methylamines and SCFAs. The novel application of hierarchical‐principal component analysis allowed visualization of multicompartmental transgenomic metabolic interactions that could also be resolved at the compartment and pathway level. These integrated system investigations demonstrate the potential of metabolic profiling as a top‐down systems biology driver for investigating the mechanistic basis of probiotic action and the therapeutic surveillance of the gut microbial activity related to dietary supplementation of probiotics.     

Dynamic compression counteracts IL-1β induced inducible nitric oxide synthase and cyclo-oxygenase-2 expression in chondrocyte/agarose constructs

Background  

Nitric oxide and prostaglandin E₂ (PGE₂play pivotal roles in both the pathogenesis of osteoarthritis and catabolic processes in articular cartilage. These mediators are influenced by both IL-1β and mechanical loading, and involve alterations in the inducible nitric oxide synthase (iNOS) and cyclo-oxygenase (COX)-2 enzymes. To identify the specific interactions that are activated by both types of stimuli, we examined the effects of dynamic compression on levels of expression of iNOS and COX-2 and involvement of the p38 mitogen-activated protein kinase (MAPK) pathway.     

Focusing on the genetics of hearing: you ain't heard nothin' yet

The complexity of genetic pathways for hearing is beginning to be amenable to unraveling by systematic functional genomic analysis. Genome-wide mutagenesis studies in the mouse are beginning to shed further light on the structure and regulation of the machinery of hearing.     

Exploring the sequence-structure protein landscape in the glycosyltransferase family

To understand the molecular basis of glycosyltransferases' (GTFs) catalytic mechanism, extensive structural information is required. Here, fold recognition methods were employed to assign 3D protein shapes (folds) to the currently known GTF sequences, available in public databases such as GenBank and Swissprot. First, GTF sequences were retrieved and classified into clusters, based on sequence similarity only. Intracluster sequence similarity was chosen sufficiently high to ensure that the same fold is found within a given cluster. Then, a representative sequence from each cluster was selected to compose a subset of GTF sequences. The members of this reduced set were processed by three different fold recognition methods: 3D-PSSM, FUGUE, and GeneFold. Finally, the results from different fold recognition methods were analyzed and compared to sequence-similarity search methods (i.e., BLAST and PSI-BLAST). It was established that the folds of about 70% of all currently known GTF sequences can be confidently assigned by fold recognition methods, a value which is higher than the fold identification rate based on sequence comparison alone (48% for BLAST and 64% for PSI-BLAST). The identified folds were submitted to 3D clustering, and we found that most of the GTF sequences adopt the typical GTF A or GTF B folds. Our results indicate a lack of evidence that new GTF folds (i.e., folds other than GTF A and B) exist. Based on cases where fold identification was not possible, we suggest several sequences as the most promising targets for a structural genomics initiative focused on the GTF protein family.