Formulating genome-scale kinetic models in the post-genome era.

The biological community is now awash in high-throughput data sets and is grappling with the challenge of integrating disparate data sets. Such integration has taken the form of statistical analysis of large data sets, or through the bottom-up reconstruction of reaction networks. While progress has been made with statistical and structural methods, large-scale systems have remained refractory to dynamic model building by traditional approaches. The availability of annotated genomes enabled the reconstruction of genome-scale networks, and now the availability of high-throughput metabolomic and fluxomic data along with thermodynamic information opens the possibility to build genome-scale kinetic models. We describe here a framework for building and analyzing such models. The mathematical analysis challenges are reflected in four foundational properties, (i) the decomposition of the Jacobian matrix into chemical, kinetic and thermodynamic information, (ii) the structural similarity between the stoichiometric matrix and the transpose of the gradient matrix, (iii) the duality transformations enabling either fluxes or concentrations to serve as the independent variables and (iv) the timescale hierarchy in biological networks. Recognition and appreciation of these properties highlight notable and challenging new in silico analysis issues

Obese patients with a binge eating disorder have an unfavorable metabolic and inflammatory profile

To evaluate whether obese patients with a binge eating disorder (BED) have an altered metabolic and inflammatory profile related to their eating behaviors compared with non-BED obese.A total of 115 White obese patients consecutively recruited underwent biochemical, anthropometrical evaluation, and a 75-g oral glucose tolerance test. Patients answered the Binge Eating Scale and were interviewed by a psychiatrist. The patients were subsequently divided into 2 groups according to diagnosis: non-BED obese (n = 85) and BED obese (n = 30). Structural equation modeling analysis was performed to elucidate the relation between eating behaviors and metabolic and inflammatory profile.BED obese exhibited significantly higher percentages of altered eating behaviors, body mass index (P < 0.001), waist circumference (P < 0.01), fat mass (P < 0.001), and a lower lean mass (P < 0.001) when compared with non-BED obese. Binge eating disorder obese also had a worse metabolic and inflammatory profile, exhibiting significantly lower high-density lipoprotein cholesterol levels (P < 0.05), and higher levels of glycated hemoglobin (P < 0.01), uric acid (P < 0.05), erythrocyte sedimentation rate (P < 0.001), high-sensitive C-reactive protein (P < 0.01), and white blood cell counts (P < 0.01). Higher fasting insulin (P < 0.01) and higher insulin resistance (P < 0.01), assessed by homeostasis model assessment index and visceral adiposity index (P < 0.001), were observed among BED obese. All differences remained significant after adjusting for body mass index. No significant differences in fasting plasma glucose or 2-hour postchallenge plasma glucose were found. Structural equation modeling analysis confirmed the relation between the altered eating behaviors of BED and the metabolic and inflammatory profile.Binge eating disorder obese exhibited an unfavorable metabolic and inflammatory profile, which is related to their characteristic eating habits

Introduction to protein folding for physicists

The prediction of the three-dimensional native structure of proteins from the knowledge of their amino acid sequence, known as the protein folding problem, is one of the most important yet unsolved issues of modern science. Since the conformational behaviour of flexible molecules is nothing more than a complex physical problem, increasingly more physicists are moving into the study of protein systems, bringing with them powerful mathematical and computational tools, as well as the sharp intuition and deep images inherent to the physics discipline. This work attempts to facilitate the first steps of such a transition. In order to achieve this goal, we provide an exhaustive account of the reasons underlying the protein folding problem enormous relevance and summarize the present-day status of the methods aimed to solving it. We also provide an introduction to the particular structure of these biological heteropolymers, and we physically define the problem stating the assumptions behind this (commonly implicit) definition. Finally, we review the 'special flavor' of statistical mechanics that is typically used to study the astronomically large phase spaces of macromolecules. Throughout the whole work, much material that is found scattered in the literature has been put together here to improve comprehension and to serve as a handy reference.Comment: 53 pages, 18 figures, the figures are at a low resolution due to arXiv restrictions, for high-res figures, go to http://www.pabloechenique.co

Pathways to interleukin-6 in healthy males and serious leisure male athletes: physical activity, body composition and age.

Physical activity (PA) is beneficial to overall health, in part due to physiological changes that lower risk factors for cardiovascular disease, including reduced inflammation. However, the mechanism by which PA reduces inflammation is unclear. One possible pathway is that PA improves body composition which in turn reduces inflammation. To test this hypothesis, we used structural equation modeling (SEM) to assess PA-body composition -inflammation pathways, as well as influences of age. In a sample of 72 healthy males with a range of PA profiles (age 18-65, mean ± sd = ), we measured PA as metabolic equivalent tasks (as per the International PA Questionnaire), body composition as percent body fat, lean mass, and fat mass, and inflammation as plasma interleukin-6 (IL-6). We treated body composition in the SEM analysis as a latent variable indicated by the three measures. We performed statistical corrections for missing values and one outlier. The model demonstrated significant effects of PA on IL-6 both directly and through body composition. Percent body fat, fat mass, and lean mass were significant indicators of the body composition latent variable. Additionally, age showed an indirect effect on IL-6 through body composition, but no direct effect. The findings suggest that PA does improve inflammatory profile through improving body composition, but that other pathways also exist

Current advances in systems and integrative biology

Systems biology has gained a tremendous amount of interest in the last few years. This is partly due to the realization that traditional approaches focusing only on a few molecules at a time cannot describe the impact of aberrant or modulated molecular environments across a whole system. Furthermore, a hypothesis-driven study aims to prove or disprove its postulations, whereas a hypothesis-free systems approach can yield an unbiased and novel testable hypothesis as an end-result. This latter approach foregoes assumptions which predict how a biological system should react to an altered microenvironment within a cellular context, across a tissue or impacting on distant organs. Additionally, re-use of existing data by systematic data mining and re-stratification, one of the cornerstones of integrative systems biology, is also gaining attention. While tremendous efforts using a systems methodology have already yielded excellent results, it is apparent that a lack of suitable analytic tools and purpose-built databases poses a major bottleneck in applying a systematic workflow. This review addresses the current approaches used in systems analysis and obstacles often encountered in large-scale data analysis and integration which tend to go unnoticed, but have a direct impact on the final outcome of a systems approach. Its wide applicability, ranging from basic research, disease descriptors, pharmacological studies, to personalized medicine, makes this emerging approach well suited to address biological and medical questions where conventional methods are not ideal

Impact of template backbone heterogeneity on RNA polymerase II transcription.

Variations in the sugar component (ribose or deoxyribose) and the nature of the phosphodiester linkage (3'-5' or 2'-5' orientation) have been a challenge for genetic information transfer from the very beginning of evolution. RNA polymerase II (pol II) governs the transcription of DNA into precursor mRNA in all eukaryotic cells. How pol II recognizes DNA template backbone (phosphodiester linkage and sugar) and whether it tolerates the backbone heterogeneity remain elusive. Such knowledge is not only important for elucidating the chemical basis of transcriptional fidelity but also provides new insights into molecular evolution. In this study, we systematically and quantitatively investigated pol II transcriptional behaviors through different template backbone variants. We revealed that pol II can well tolerate and bypass sugar heterogeneity sites at the template but stalls at phosphodiester linkage heterogeneity sites. The distinct impacts of these two backbone components on pol II transcription reveal the molecular basis of template recognition during pol II transcription and provide the evolutionary insight from the RNA world to the contemporary 'imperfect' DNA world. In addition, our results also reveal the transcriptional consequences from ribose-containing genomic DNA

A novel bacterial l-arginine sensor controlling c-di-GMP levels in Pseudomonas aeruginosa

Nutrients such as amino acids play key roles in shaping the metabolism of microorganisms in natural environments and in host–pathogen interactions. Beyond taking part to cellular metabolism and to protein synthesis, amino acids are also signaling molecules able to influence group behavior in microorganisms, such as biofilm formation. This lifestyle switch involves complex metabolic reprogramming controlled by local variation of the second messenger 3′, 5′-cyclic diguanylic acid (c-di-GMP). The intracellular levels of this dinucleotide are finely tuned by the opposite activity of dedicated diguanylate cyclases (GGDEF signature) and phosphodiesterases (EAL and HD-GYP signatures), which are usually allosterically controlled by a plethora of environmental and metabolic clues. Among the genes putatively involved in controlling c-di-GMP levels in P. aeruginosa, we found that the multidomain transmembrane protein PA0575, bearing the tandem signature GGDEF-EAL, is an l-arginine sensor able to hydrolyse c-di-GMP. Here, we investigate the basis of arginine recognition by integrating bioinformatics, molecular biophysics and microbiology. Although the role of nutrients such as l-arginine in controlling the cellular fate in P. aeruginosa (including biofilm, pathogenicity and virulence) is already well established, we identified the first l-arginine sensor able to link environment sensing, c-di-GMP signaling and biofilm formation in this bacterium