Reverse Engineering Gene Networks with ANN: Variability in Network Inference Algorithms

Motivation :Reconstructing the topology of a gene regulatory network is one of the key tasks in systems biology. Despite of the wide variety of proposed methods, very little work has been dedicated to the assessment of their stability properties. Here we present a methodical comparison of the performance of a novel method (RegnANN) for gene network inference based on multilayer perceptrons with three reference algorithms (ARACNE, CLR, KELLER), focussing our analysis on the prediction variability induced by both the network intrinsic structure and the available data. Results: The extensive evaluation on both synthetic data and a selection of gene modules of "Escherichia coli" indicates that all the algorithms suffer of instability and variability issues with regards to the reconstruction of the topology of the network. This instability makes objectively very hard the task of establishing which method performs best. Nevertheless, RegnANN shows MCC scores that compare very favorably with all the other inference methods tested. Availability: The software for the RegnANN inference algorithm is distributed under GPL3 and it is available at the corresponding author home page (http://mpba.fbk.eu/grimaldi/regnann-supmat

On tacit knowledge for philosophy of education

This article offers a detailed reading Gascoigne and Thornton’s book Tacit Knowledge (2013), which aims to account for the tacitness of tacit knowledge (TK) while preserving its status as knowledge proper. I take issue with their characterization and rejection of the existential-phenomenological Background—which they presuppose even as they dismiss—and their claim that TK can be articulated “from within”—which betrays a residual Cartesianism, the result of their elision of conceptuality and propositionality. Knowledgeable acts instantiate capacities which we might know we have and of which we can be aware, but which are not propositionally structured at their “core”. Nevertheless, propositionality is necessary to what Robert Brandom calls, in Making It Explicit (1994) and Articulating Reasons (2000), “explicitation”, which notion also presupposes a tacit dimension, which is, simply, the embodied person (the knower), without which no conception of knowledge can get any purchase. On my view, there is no knowledgeable act that can be understood as such separately from the notion of skilled corporeal performance. The account I offer cannot make sense of so-called “knowledge-based” education, as opposed to systems and styles which supposedly privilege “contentless” skills over and above “knowledge”, because on the phenomenological and inferentialist lines I endorse, neither the concepts “knowledge” nor “skill” has any purchase or meaning without the other

A Bayesian Approach to the Evolution of Metabolic Networks on a Phylogeny

The availability of genomes of many closely related bacteria with diverse metabolic capabilities offers the possibility of tracing metabolic evolution on a phylogeny relating the genomes to understand the evolutionary processes and constraints that affect the evolution of metabolic networks. Using simple (independent loss/gain of reactions) or complex (incorporating dependencies among reactions) stochastic models of metabolic evolution, it is possible to study how metabolic networks evolve over time. Here, we describe a model that takes the reaction neighborhood into account when modeling metabolic evolution. The model also allows estimation of the strength of the neighborhood effect during the course of evolution. We present Gibbs samplers for sampling networks at the internal node of a phylogeny and for estimating the parameters of evolution over a phylogeny without exploring the whole search space by iteratively sampling from the conditional distributions of the internal networks and parameters. The samplers are used to estimate the parameters of evolution of metabolic networks of bacteria in the genus Pseudomonas and to infer the metabolic networks of the ancestral pseudomonads. The results suggest that pathway maps that are conserved across the Pseudomonas phylogeny have a stronger neighborhood structure than those which have a variable distribution of reactions across the phylogeny, and that some Pseudomonas lineages are going through genome reduction resulting in the loss of a number of reactions from their metabolic networks

Protein coalitions in a core mammalian biochemical network linked by rapidly evolving proteins

<p>Abstract</p> <p>Background</p> <p>Cellular ATP levels are generated by glucose-stimulated mitochondrial metabolism and determine metabolic responses, such as glucose-stimulated insulin secretion (GSIS) from the β-cells of pancreatic islets. We describe an analysis of the evolutionary processes affecting the core enzymes involved in glucose-stimulated insulin secretion in mammals. The proteins involved in this system belong to ancient enzymatic pathways: glycolysis, the TCA cycle and oxidative phosphorylation.</p> <p>Results</p> <p>We identify two sets of proteins, or protein coalitions, in this group of 77 enzymes with distinct evolutionary patterns. Members of the glycolysis, TCA cycle, metabolite transport, pyruvate and NADH shuttles have low rates of protein sequence evolution, as inferred from a human-mouse comparison, and relatively high rates of evolutionary gene duplication. Respiratory chain and glutathione pathway proteins evolve faster, exhibiting lower rates of gene duplication. A small number of proteins in the system evolve significantly faster than co-pathway members and may serve as rapidly evolving adapters, linking groups of co-evolving genes.</p> <p>Conclusions</p> <p>Our results provide insights into the evolution of the involved proteins. We find evidence for two coalitions of proteins and the role of co-adaptation in protein evolution is identified and could be used in future research within a functional context.</p

A transcriptomic analysis of Echinococcus granulosus larval stages:implications for parasite biology and host adaptation

The cestode Echinococcus granulosus--the agent of cystic echinococcosis, a zoonosis affecting humans and domestic animals worldwide--is an excellent model for the study of host-parasite cross-talk that interfaces with two mammalian hosts. To develop the molecular analysis of these interactions, we carried out an EST survey of E. granulosus larval stages. We report the salient features of this study with a focus on genes reflecting physiological adaptations of different parasite stages.We generated ~10,000 ESTs from two sets of full-length enriched libraries (derived from oligo-capped and trans-spliced cDNAs) prepared with three parasite materials: hydatid cyst wall, larval worms (protoscoleces), and pepsin/H(+)-activated protoscoleces. The ESTs were clustered into 2700 distinct gene products. In the context of the biology of E. granulosus, our analyses reveal: (i) a diverse group of abundant long non-protein coding transcripts showing homology to a middle repetitive element (EgBRep) that could either be active molecular species or represent precursors of small RNAs (like piRNAs); (ii) an up-regulation of fermentative pathways in the tissue of the cyst wall; (iii) highly expressed thiol- and selenol-dependent antioxidant enzyme targets of thioredoxin glutathione reductase, the functional hub of redox metabolism in parasitic flatworms; (iv) candidate apomucins for the external layer of the tissue-dwelling hydatid cyst, a mucin-rich structure that is critical for survival in the intermediate host; (v) a set of tetraspanins, a protein family that appears to have expanded in the cestode lineage; and (vi) a set of platyhelminth-specific gene products that may offer targets for novel pan-platyhelminth drug development.This survey has greatly increased the quality and the quantity of the molecular information on E. granulosus and constitutes a valuable resource for gene prediction on the parasite genome and for further genomic and proteomic analyses focused on cestodes and platyhelminths

Diet, physical exercise and cognitive behavioral training as a combined workplace based intervention to reduce body weight and increase physical capacity in health care workers - a randomized controlled trial

<p>Abstract</p> <p>Background</p> <p>Health care workers comprise a high-risk workgroup with respect to deterioration and early retirement. There is high prevalence of obesity and many of the workers are overweight. Together, these factors play a significant role in the health-related problems within this sector. The present study evaluates the effects of the first 3-months of a cluster randomized controlled lifestyle intervention among health care workers. The intervention addresses body weight, general health variables, physical capacity and musculoskeletal pain.</p> <p>Methods</p> <p>98 female, overweight health care workers were cluster-randomized to an intervention group or a reference group. The intervention consisted of an individually dietary plan with an energy deficit of 1200 kcal/day (15 min/hour), strengthening exercises (15 min/hour) and cognitive behavioral training (30 min/hour) during working hours 1 hour/week. Leisure time aerobic fitness was planned for 2 hour/week. The reference group was offered monthly oral presentations. Body weight, BMI, body fat percentage (bioimpedance), waist circumference, blood pressure, musculoskeletal pain, maximal oxygen uptake (maximal bicycle test), and isometric maximal muscle strength of 3 body regions were measured before and after the intervention period.</p> <p>Results</p> <p>In an intention-to-treat analysis from pre to post tests, the intervention group significantly reduced body weight with 3.6 kg (p < 0.001), BMI from 30.5 to 29.2 (p < 0.001), body fat percentage from 40.9 to 39.3 (p < 0.001), waist circumference from 99.7 to 95.5 cm (p < 0.001) and blood pressure from 134/85 to 127/80 mmHg (p < 0.001), with significant difference between the intervention and control group (p < 0.001) on all measures. No effect of intervention was found in musculoskeletal pain, maximal oxygen uptake and muscle strength, but on aerobic fitness.</p> <p>Conclusion</p> <p>The significantly reduced body weight, body fat, waist circumference and blood pressure as well as increased aerobic fitness in the intervention group show the great potential of workplace health promotion among this high-risk workgroup. Long-term effects of the intervention remain to be investigated.</p> <p>Trial registration</p> <p>ClinicalTrials.gov: <a href="http://www.clinicaltrials.gov/ct2/show/NCT01015716">NCT01015716</a></p

A Global Characterization and Identification of Multifunctional Enzymes

Multi-functional enzymes are enzymes that perform multiple physiological functions. Characterization and identification of multi-functional enzymes are critical for communication and cooperation between different functions and pathways within a complex cellular system or between cells. In present study, we collected literature-reported 6,799 multi-functional enzymes and systematically characterized them in structural, functional, and evolutionary aspects. It was found that four physiochemical properties, that is, charge, polarizability, hydrophobicity, and solvent accessibility, are important for characterization of multi-functional enzymes. Accordingly, a combinational model of support vector machine and random forest model was constructed, based on which 6,956 potential novel multi-functional enzymes were successfully identified from the ENZYME database. Moreover, it was observed that multi-functional enzymes are non-evenly distributed in species, and that Bacteria have relatively more multi-functional enzymes than Archaebacteria and Eukaryota. Comparative analysis indicated that the multi-functional enzymes experienced a fluctuation of gene gain and loss during the evolution from S. cerevisiae to H. sapiens. Further pathway analyses indicated that a majority of multi-functional enzymes were well preserved in catalyzing several essential cellular processes, for example, metabolisms of carbohydrates, nucleotides, and amino acids. What’s more, a database of known multi-functional enzymes and a server for novel multi-functional enzyme prediction were also constructed for free access at http://bioinf.xmu.edu.cn/databases/MFEs/index.htm

Effect of Peripheral 5-HT on Glucose and Lipid Metabolism in Wether Sheep

In mice, peripheral 5-HT induces an increase in the plasma concentrations of glucose, insulin and bile acids, and a decrease in plasma triglyceride, NEFA and cholesterol concentrations. However, given the unique characteristics of the metabolism of ruminants relative to monogastric animals, the physiological role of peripheral 5-HT on glucose and lipid metabolism in sheep remains to be established. Therefore, in this study, we investigated the effect of 5-HT on the circulating concentrations of metabolites and insulin using five 5-HT receptor (5HTR) antagonists in sheep. After fasting for 24 h, sheep were intravenously injected with 5-HT, following which-, plasma glucose, insulin, triglyceride and NEFA concentrations were significantly elevated. In contrast, 5-HT did not affect the plasma cholesterol concentration, and it induced a decrease in bile acid concentrations. Increases in plasma glucose and insulin concentrations induced by 5-HT were attenuated by pre-treatment with Methysergide, a 5HTR 1, 2 and 7 antagonist. Additionally, decreased plasma bile acid concentrations induced by 5-HT were blocked by pre-treatment with Ketanserin, a 5HTR 2A antagonist. However, none of the 5HTR antagonists inhibited the increase in plasma triglyceride and NEFA levels induced by 5-HT. On the other hand, mRNA expressions of 5HTR1D and 1E were observed in the liver, pancreas and skeletal muscle. These results suggest that there are a number of differences in the physiological functions of peripheral 5-HT with respect to lipid metabolism between mice and sheep, though its effect on glucose metabolism appears to be similar between these species

A Scalable Approach for Discovering Conserved Active Subnetworks across Species

Overlaying differential changes in gene expression on protein interaction networks has proven to be a useful approach to interpreting the cell's dynamic response to a changing environment. Despite successes in finding active subnetworks in the context of a single species, the idea of overlaying lists of differentially expressed genes on networks has not yet been extended to support the analysis of multiple species' interaction networks. To address this problem, we designed a scalable, cross-species network search algorithm, neXus (Network - cross(X)-species - Search), that discovers conserved, active subnetworks based on parallel differential expression studies in multiple species. Our approach leverages functional linkage networks, which provide more comprehensive coverage of functional relationships than physical interaction networks by combining heterogeneous types of genomic data. We applied our cross-species approach to identify conserved modules that are differentially active in stem cells relative to differentiated cells based on parallel gene expression studies and functional linkage networks from mouse and human. We find hundreds of conserved active subnetworks enriched for stem cell-associated functions such as cell cycle, DNA repair, and chromatin modification processes. Using a variation of this approach, we also find a number of species-specific networks, which likely reflect mechanisms of stem cell function that have diverged between mouse and human. We assess the statistical significance of the subnetworks by comparing them with subnetworks discovered on random permutations of the differential expression data. We also describe several case examples that illustrate the utility of comparative analysis of active subnetworks