Except for conversion to bile salts, there is no major cholesterol degradation pathway in mammals. Efficient excretion from the body is therefore a crucial element in cholesterol homeostasis. Yet, the existence and importance of cholesterol degradation pathways in humans is a matter of debate. We quantified cholesterol fluxes in 15 male volunteers using a cholesterol balance approach. Ten participants repeated the protocol after 4 weeks of treatment with ezetimibe, an inhibitor of intestinal and biliary cholesterol absorption. Under basal conditions, about 65% of daily fecal neutral sterol excretion was bile derived, with the remainder being contributed by direct transintestinal cholesterol excretion (TICE). Surprisingly, ezetimibe induced a 4-fold increase in cholesterol elimination via TICE. Mouse studies revealed that most of ezetimibe-induced TICE flux is mediated by the cholesterol transporter Abcg5/Abcg8. In conclusion, TICE is active in humans and may serve as a novel target to stimulate cholesterol elimination in patients at risk for cardiovascular disease.

Nonribosomally and ribosomally synthesized bioactive peptides constitute a source of molecules of great biomedical importance, including antibiotics such as penicillin, immunosuppressants such as cyclosporine, and cytostatics such as bleomycin. Recently, an innovative mass-spectrometry-based strategy, peptidogenomics, has been pioneered to effectively mine microbial strains for novel peptidic metabolites. Even though mass-spectrometric peptide detection can be performed quite fast, true high-throughput natural product discovery approaches have still been limited by the inability to rapidly match the identified tandem mass spectra to the gene clusters responsible for the biosynthesis of the corresponding compounds. With Pep2Path, we introduce a software package to fully automate the peptidogenomics approach through the rapid Bayesian probabilistic matching of mass spectra to their corresponding biosynthetic gene clusters. Detailed benchmarking of the method shows that the approach is powerful enough to correctly identify gene clusters even in data sets that consist of hundreds of genomes, which also makes it possible to match compounds from unsequenced organisms to closely related biosynthetic gene clusters in other genomes. Applying Pep2Path to a data set of compounds without known biosynthesis routes, we were able to identify candidate gene clusters for the biosynthesis of five important compounds. Notably, one of these clusters was detected in a genome from a different subphylum of Proteobacteria than that in which the molecule had first been identified. All in all, our approach paves the way towards high-throughput discovery of novel peptidic natural products. Pep2Path is freely available from http://pep2path.sourceforge.net/, implemented in Python, licensed under the GNU General Public License v3 and supported on MS Windows, Linux and Mac OS X.

Physiological adaptations resulting in the development of the metabolic syndrome in man occur over a time span of several decades. This combined with the prohibitive financial cost and ethical concerns to measure key metabolic parameters repeatedly in subjects for the major part of their life span makes that comprehensive longitudinal human data sets are virtually nonexistent. While experimental mice are often used, little is known whether this species is in fact an adequate model to better understand the mechanisms that drive the metabolic syndrome in man. We took up the challenge to study the response of male apoE*3‐Leiden.CETP mice (with a humanized lipid profile) to a high‐fat high‐cholesterol diet for 6 months. Study parameters include body weight, food intake, plasma and liver lipids, hepatic transcriptome, VLDL – triglyceride production and importantly the use of stable isotopes to measure hepatic de novo lipogenesis, gluconeogenesis, and biliary/fecal sterol secretion to assess metabolic fluxes. The key observations include (1) high inter‐individual variation; (2) a largely unaffected hepatic transcriptome at 2, 3, and 6 months; (3) a biphasic response curve of the main metabolic features over time; and (4) maximum insulin resistance preceding dyslipidemia. The biphasic response in plasma triglyceride and total cholesterol appears to mimic that of men in cross‐sectional studies. Combined, these observations suggest that studies such as these can help to delineate the causes of metabolic derangements in patients suffering from metabolic syndrome.

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