Gene expression model (in)validation by Fourier analysis

The determination of the right model structure describing a gene regulation network and the identification of its parameters are major goals in systems biology. The task is often hampered by the lack of relevant experimental data with sufficiently low noise level, but the subset of genes whose concentration levels exhibit an oscillatory behavior in time can readily be analyzed on the basis of their Fourier spectrum, known to turn complex signals into few relatively noise-free parameters. Such genes therefore offer opportunities of understanding gene regulation quantitatively.Journal ArticleResearch Support, Non-U.S. Gov'tValidation StudiesSCOPUS: ar.jinfo:eu-repo/semantics/publishe

Achieving Optimal Growth through Product Feedback Inhibition in Metabolism

Recent evidence suggests that the metabolism of some organisms, such as Escherichia coli, is remarkably efficient, producing close to the maximum amount of biomass per unit of nutrient consumed. This observation raises the question of what regulatory mechanisms enable such efficiency. Here, we propose that simple product-feedback inhibition by itself is capable of leading to such optimality. We analyze several representative metabolic modules—starting from a linear pathway and advancing to a bidirectional pathway and metabolic cycle, and finally to integration of two different nutrient inputs. In each case, our mathematical analysis shows that product-feedback inhibition is not only homeostatic but also, with appropriate feedback connections, can minimize futile cycling and optimize fluxes. However, the effectiveness of simple product-feedback inhibition comes at the cost of high levels of some metabolite pools, potentially associated with toxicity and osmotic imbalance. These large metabolite pool sizes can be restricted if feedback inhibition is ultrasensitive. Indeed, the multi-layer regulation of metabolism by control of enzyme expression, enzyme covalent modification, and allostery is expected to result in such ultrasensitive feedbacks. To experimentally test whether the qualitative predictions from our analysis of feedback inhibition apply to metabolic modules beyond linear pathways, we examine the case of nitrogen assimilation in E. coli, which involves both nutrient integration and a metabolic cycle. We find that the feedback regulation scheme suggested by our mathematical analysis closely aligns with the actual regulation of the network and is sufficient to explain much of the dynamical behavior of relevant metabolite pool sizes in nutrient-switching experiments

A review of elliptical and disc galaxy structure, and modern scaling laws

A century ago, in 1911 and 1913, Plummer and then Reynolds introduced their models to describe the radial distribution of stars in `nebulae'. This article reviews the progress since then, providing both an historical perspective and a contemporary review of the stellar structure of bulges, discs and elliptical galaxies. The quantification of galaxy nuclei, such as central mass deficits and excess nuclear light, plus the structure of dark matter halos and cD galaxy envelopes, are discussed. Issues pertaining to spiral galaxies including dust, bulge-to-disc ratios, bulgeless galaxies, bars and the identification of pseudobulges are also reviewed. An array of modern scaling relations involving sizes, luminosities, surface brightnesses and stellar concentrations are presented, many of which are shown to be curved. These 'redshift zero' relations not only quantify the behavior and nature of galaxies in the Universe today, but are the modern benchmark for evolutionary studies of galaxies, whether based on observations, N-body-simulations or semi-analytical modelling. For example, it is shown that some of the recently discovered compact elliptical galaxies at 1.5 < z < 2.5 may be the bulges of modern disc galaxies.Comment: Condensed version (due to Contract) of an invited review article to appear in "Planets, Stars and Stellar Systems"(www.springer.com/astronomy/book/978-90-481-8818-5). 500+ references incl. many somewhat forgotten, pioneer papers. Original submission to Springer: 07-June-201

The acceptance of the clinical photographic posture assessment tool (CPPAT)

Abstract Background There is a lack of evidence-based quantitative clinical methods to adequately assess posture. Our team developed a clinical photographic posture assessment tool (CPPAT) and implemented this tool in clinical practice to standardize posture assessment. The objectives were to determine the level of acceptance of the CPPAT and to document predictors as well as facilitators of and barriers to the acceptance of this tool by clinicians doing posture re-education. Methods This is a prospective study focussing on technology acceptance. Thirty-two clinician participants (physical therapists and sport therapists) received a 3–5 h training workshop explaining how to use the CPPAT. Over a three-month trial, they recorded time-on-task for a complete posture evaluation (photo - and photo-processing). Subsequently, participants rated their acceptance of the tool and commented on facilitators and barriers of the clinical method. Results Twenty-three clinician participants completed the trial. They took 22 (mean) ± 10 min (SD) for photo acquisition and 36 min ± 19 min for photo-processing. Acceptance of the CPPAT was high. Perceived ease of use was an indirect predictor of intention to use, mediated by perceived usefulness. Analysis time was an indirect predictor, mediated by perceived usefulness, and a marginally significant direct predictor. Principal facilitators were objective measurements, visualization, utility, and ease of use. Barriers were time to do a complete analysis of posture, quality of human-computer interaction, non-automation of posture index calculation and photo transfer, and lack of versatility. Conclusion The CPPAT is perceived as useful and easy to use by clinicians and may facilitate the quantitative analysis of posture. Adapting the user-interface and functionality to quantify posture may facilitate a wider adoption of the tool

Nasty Viruses, Costly Plasmids, Population Dynamics, and the Conditions for Establishing and Maintaining CRISPR-Mediated Adaptive Immunity in Bacteria

Clustered, Regularly Interspaced Short Palindromic Repeats (CRISPR) abound in the genomes of almost all archaebacteria and nearly half the eubacteria sequenced. Through a genetic interference mechanism, bacteria with CRISPR regions carrying copies of the DNA of previously encountered phage and plasmids abort the replication of phage and plasmids with these sequences. Thus it would seem that protection against infecting phage and plasmids is the selection pressure responsible for establishing and maintaining CRISPR in bacterial populations. But is it? To address this question and provide a framework and hypotheses for the experimental study of the ecology and evolution of CRISPR, I use mathematical models of the population dynamics of CRISPR-encoding bacteria with lytic phage and conjugative plasmids. The results of the numerical (computer simulation) analysis of the properties of these models with parameters in the ranges estimated for Escherichia coli and its phage and conjugative plasmids indicate: (1) In the presence of lytic phage there are broad conditions where bacteria with CRISPR-mediated immunity will have an advantage in competition with non-CRISPR bacteria with otherwise higher Malthusian fitness. (2) These conditions for the existence of CRISPR are narrower when there is envelope resistance to the phage. (3) While there are situations where CRISPR-mediated immunity can provide bacteria an advantage in competition with higher Malthusian fitness bacteria bearing deleterious conjugative plasmids, the conditions for this to obtain are relatively narrow and the intensity of selection favoring CRISPR weak. The parameters of these models can be independently estimated, the assumption behind their construction validated, and the hypotheses generated from the analysis of their properties tested in experimental populations of bacteria with lytic phage and conjugative plasmids. I suggest protocols for estimating these parameters and outline the design of experiments to evaluate the validity of these models and test these hypotheses

CLOTU: An online pipeline for processing and clustering of 454 amplicon reads into OTUs followed by taxonomic annotation

<p>Abstract</p> <p>Background</p> <p>The implementation of high throughput sequencing for exploring biodiversity poses high demands on bioinformatics applications for automated data processing. Here we introduce <smcaps>CLOTU</smcaps>, an online and open access pipeline for processing 454 amplicon reads. C<smcaps>LOTU</smcaps> has been constructed to be highly user-friendly and flexible, since different types of analyses are needed for different datasets.</p> <p>Results</p> <p>In <smcaps>CLOTU</smcaps>, the user can filter out low quality sequences, trim tags, primers, adaptors, perform clustering of sequence reads, and run <smcaps>BLAST</smcaps> against NCBInr or a customized database in a high performance computing environment. The resulting data may be browsed in a user-friendly manner and easily forwarded to downstream analyses. Although <smcaps>CLOTU</smcaps> is specifically designed for analyzing 454 amplicon reads, other types of DNA sequence data can also be processed. A fungal ITS sequence dataset generated by 454 sequencing of environmental samples is used to demonstrate the utility of <smcaps>CLOTU</smcaps>.</p> <p>Conclusions</p> <p>C<smcaps>LOTU</smcaps> is a flexible and easy to use bioinformatics pipeline that includes different options for filtering, trimming, clustering and taxonomic annotation of high throughput sequence reads. Some of these options are not included in comparable pipelines. C<smcaps>LOTU</smcaps> is implemented in a Linux computer cluster and is freely accessible to academic users through the Bioportal web-based bioinformatics service (<url>http://www.bioportal.uio.no</url>).</p

Synergy Between Intercellular Communication and Intracellular Ca2+ Handling in Arrhythmogenesis

Calcium is the primary signalling component of excitation-contraction coupling, the process linking electrical excitability of cardiac muscle cells to coordinated contraction of the heart. Understanding Ca2þ handling processes at the cellular level and the role of intercellular communication in the emergence of multicellular synchronization are key aspects in the study of arrhythmias. To probe these mechanisms, we have simulated cellular interactions on large scale arrays that mimic cardiac tissue, and where individual cells are represented by a mathematical model of intracellular Ca2þ dynamics. Theoretical predictions successfully reproduced experimental findings and provide novel insights on the action of two pharmacological agents (ionomycin and verapamil) that modulate Ca2þ signalling pathways via distinct mechanisms. Computational results have demonstrated how transitions between local synchronisation events and large scale wave formation are affected by these agents. Entrainment phenomena are shown to be linked to both ntracellular Ca2þ and coupling-specific dynamics in a synergistic manner. The intrinsic variability of the cellular matrix is also shown to affect emergent patterns of rhythmicity, providing insights into the origins of arrhythmogenic Ca2þ perturbations in cardiac tissue in situ

Accurate Genome Relative Abundance Estimation Based on Shotgun Metagenomic Reads

Accurate estimation of microbial community composition based on metagenomic sequencing data is fundamental for subsequent metagenomics analysis. Prevalent estimation methods are mainly based on directly summarizing alignment results or its variants; often result in biased and/or unstable estimates. We have developed a unified probabilistic framework (named GRAMMy) by explicitly modeling read assignment ambiguities, genome size biases and read distributions along the genomes. Maximum likelihood method is employed to compute Genome Relative Abundance of microbial communities using the Mixture Model theory (GRAMMy). GRAMMy has been demonstrated to give estimates that are accurate and robust across both simulated and real read benchmark datasets. We applied GRAMMy to a collection of 34 metagenomic read sets from four metagenomics projects and identified 99 frequent species (minimally 0.5% abundant in at least 50% of the data- sets) in the human gut samples. Our results show substantial improvements over previous studies, such as adjusting the over-estimated abundance for Bacteroides species for human gut samples, by providing a new reference-based strategy for metagenomic sample comparisons. GRAMMy can be used flexibly with many read assignment tools (mapping, alignment or composition-based) even with low-sensitivity mapping results from huge short-read datasets. It will be increasingly useful as an accurate and robust tool for abundance estimation with the growing size of read sets and the expanding database of reference genomes