Targeted proteomics reveals strain‐specific changes in the mouse insulin and central metabolic pathways after a sustained high‐fat diet

The metabolic syndrome is a collection of risk factors including obesity, insulin resistance and hepatic steatosis, which occur together and increase the risk of diseases such as diabetes, cardiovascular disease and cancer. In spite of intense research, the complex etiology of insulin resistance and its association with the accumulation of triacylglycerides in the liver and with hepatic steatosis remains not completely understood. Here, we performed quantitative measurements of 144 proteins involved in the insulin‐signaling pathway and central metabolism in liver homogenates of two genetically well‐defined mouse strains C57BL/6J and 129Sv that were subjected to a sustained high‐fat diet. We used targeted mass spectrometry by selected reaction monitoring (SRM) to generate accurate and reproducible quantitation of the targeted proteins across 36 different samples (12 conditions and 3 biological replicates), generating one of the largest quantitative targeted proteomics data sets in mammalian tissues. Our results revealed rapid response to high‐fat diet that diverged early in the feeding regimen, and evidenced a response to high‐fat diet dominated by the activation of peroxisomal β‐oxidation in C57BL/6J and by lipogenesis in 129Sv mice.     

Egg production of individual copepods of Acartia grani Sars from coastal waters: seasonal and diel variability

Seasonal and diel fecundity patterns of adult Acartia granifemales from a coastal area of Malaga Bay (south of Spain) werestudied between spring and autumn 1990. Copepod egg productionwas measured in situ by short-term (     

AlignMiner: a Web-based tool for detection of divergent regions in multiple sequence alignments of conserved sequences

Background  

Multiple sequence alignments are used to study gene or protein function, phylogenetic relations, genome evolution hypotheses and even gene polymorphisms. Virtually without exception, all available tools focus on conserved segments or residues. Small divergent regions, however, are biologically important for specific quantitative polymerase chain reaction, genotyping, molecular markers and preparation of specific antibodies, and yet have received little attention. As a consequence, they must be selected empirically by the researcher. AlignMiner has been developed to fill this gap in bioinformatic analyses.