Cardiolipin Supports Respiratory Enzymes in Plants in Different Ways.

In eukaryotes the presence of the dimeric phospholipid cardiolipin (CL) is limited to the mitochondrial membranes. It resides predominantly in the inner membrane where it interacts with components of the mitochondrial electron transfer chain. CL deficiency has previously been shown to affect abundances of the plant NADH-dehydrogenase complex and its association with dimeric cyctochrome c reductase. Using an Arabidopsis thaliana knock-out mutant for the final enzyme of CL biosynthesis we here extend current knowledge on the dependence of plant respiration on CL. By correlating respiratory enzyme abundances with enzymatic capacities in mitochondria isolated from wild type, CL deficient and CL complemented heterotrophic cell culture lines a new picture of the participation of CL in plant respiration is emerging. Data indicate a loss of a general reduction of respiratory capacity in CL deficient mitochondria which cannot solely be attributed to decreased abundances or capacities of mitochondrial electron transfer protein complexes and supercomplexes. Instead, it most likely is the result of a loss of the mobile electron carrier cytochrome c. Furthermore, enzymes of the tricarboxylic acid cycle are found to have lower maximum activities in the mutant, including the succinate dehydrogenase complex. Interestingly, abundance of the latter is not altered, indicative of a direct impact of CL deficiency on the enzymatic capacity of this electron transfer chain protein complex.

A General Framework for the Evaluation of Genetic Association Studies Using Multiple Marginal Models.

OBJECTIVE: In this study, we present a simultaneous inference procedure as a unified analysis framework for genetic association studies. METHODS: The method is based on the formulation of multiple marginal models that reflect different modes of inheritance. The basic advantage of this methodology is that no explicit formulation of the correlation between the test statistics is required. Moreover, the genotype scores are considered as a quantitative explanatory variable, i.e., regression models are used. RESULTS: The proposed approach covers a wide variety of endpoints (binary, count, quantitative, and time-to-event data). In addition, multiple endpoints of different types can be assessed simultaneously. This allows the detection of pleiotropic effects while taking the mode of inheritance into account. Moreover, multiple loci can be assessed simultaneously. CONCLUSION: The flexibility of the proposed approach is demonstrated while analyzing a variety of data examples.

Isolation, Structure Elucidation, Biosynthesis, and Synthesis of Antalid, a Secondary Metabolite from Polyangium species.

The isolation, structure elucidation, and synthesis of antalid (1), a novel secondary metabolite from Polyangium sp., is described herein. The structure elucidation of 1 was performed with the aid of mass spectrometry, high field NMR experiments, and crystal structure analysis. The absolute configuration of antalid was confirmed through the Mosher ester method and ultimately by total synthesis. In addition, the biosynthetic origin of this hybrid PKS-NRPS natural product was unraveled by the in silico analysis of its biosynthetic gene cluster.

Detecting qualitative interactions in clinical trials with binary responses.

This study considers the detection of treatment-by-subset interactions in a stratified, randomised clinical trial with a binary-response variable. The focus lies on the detection of qualitative interactions. In addition, the presented method is useful more generally, as it can assess the inconsistency of the treatment effects among strata by using an a priori-defined inconsistency margin. The methodology presented is based on the construction of ratios of treatment effects. In addition to multiplicity-adjusted p-values, simultaneous confidence intervals are recommended to use in detecting the source and the amount of a potential qualitative interaction. The proposed method is demonstrated on a multi-regional trial using the open-source statistical software R.

Testing for qualitative interaction using ratios of treatment differences.

Testing for or against a qualitative interaction is relevant in randomized clinical trials that use a common primary factor treatment and have a secondary factor, such as the centre, region, subgroup, gender or biomarker. Interaction contrasts are formulated for ratios of differences between the levels of the primary treatment factor. Simultaneous confidence intervals allow for interpreting the magnitude and the relevance of the qualitative interaction. The proposed method is demonstrated by means of a multi-centre clinical trial, using the R package mratios.

Configurational assignment of secondary hydroxyl groups and methyl branches in polyketide natural products through bioinformatic analysis of the ketoreductase domain.

Profile hidden Markov models (HMMs) were used to predict the configuration of secondary alcohols and α-methyl branches of modular polyketides. Based on the configurations of two chiral centers in these polyketides, 78 ketoreductases were classified into four different types of polyketide producers. The identification of positions that discriminate between these protein families was followed by fitting six profile HMMs to the data set and the corresponding subsets, to model the conserved regions of the protein types. Ultimately, the profile HMMs described herein predict protein subtypes based on the complete information-rich region; consequently, slight changes in a multiple sequence alignment do not significantly alter the outcome of this classification method. Additionally, Viterbi scores can be used to assess the reliability of the classification.