Computational models in systems biology

A report of the 6th International Conference on Computational Methods in Systems Biology, Rostock, Germany, 12-15 October 2008

Design and Development of Software Tools for Bio-PEPA

This paper surveys the design of software tools for the Bio-PEPA process algebra. Bio-PEPA is a high-level language for modelling biological systems such as metabolic pathways and other biochemical reaction networks. Through providing tools for this modelling language we hope to allow easier use of a range of simulators and model-checkers thereby freeing the modeller from the responsibility of developing a custom simulator for the problem of interest. Further, by providing mappings to a range of different analysis tools the Bio-PEPA language allows modellers to compare analysis results which have been computed using independent numerical analysers, which enhances the reliability and robustness of the results computed.

On the potential for extinction by Muller's Ratchet in Caenorhabditis elegans

<p>Abstract</p> <p>Background</p> <p>The self-fertile hermaphrodite worm <it>C. elegans </it>is an important model organism for biology, yet little is known about the origin and persistence of the self-fertilizing mode of reproduction in this lineage. Recent work has demonstrated an extraordinary degree of selfing combined with a high deleterious mutation rate in contemporary populations. These observations raise the question as to whether the mutation load might rise to such a degree as to eventually threaten the species with extinction. The potential for such a process to occur would inform our understanding of the time since the origin of self-fertilization in <it>C. elegans </it>history.</p> <p>Results</p> <p>To address this issue, here we quantify the rate of fitness decline expected to occur via Muller's ratchet for a purely selfing population, using both analytical approximations and globally distributed individual-based simulations from the evolution@home system to compute the rate of deleterious mutation accumulation. Using the best available estimates for parameters of how <it>C. elegans </it>evolves, we conclude that pure selfing can persist for only short evolutionary intervals, and is expected to lead to extinction within thousands of years for a plausible portion of parameter space. Credible lower-bound estimates of nuclear mutation rates do not extend the expected time to extinction much beyond a million years.</p> <p>Conclusion</p> <p>Thus we conclude that either the extreme self-fertilization implied by current patterns of genetic variation in <it>C. elegans </it>arose relatively recently or that low levels of outcrossing and other factors are key to the persistence of <it>C. elegans </it>into the present day. We also discuss results for the mitochondrial genome and the implications for <it>C. briggsae</it>, a close relative that made the transition to selfing independently of <it>C. elegans</it>.</p

Quantifying the implicit process flow abstraction in SBGN-PD diagrams with Bio-PEPA

For a long time biologists have used visual representations of biochemical networks to gain a quick overview of important structural properties. Recently SBGN, the Systems Biology Graphical Notation, has been developed to standardise the way in which such graphical maps are drawn in order to facilitate the exchange of information. Its qualitative Process Diagrams (SBGN-PD) are based on an implicit Process Flow Abstraction (PFA) that can also be used to construct quantitative representations, which can be used for automated analyses of the system. Here we explicitly describe the PFA that underpins SBGN-PD and define attributes for SBGN-PD glyphs that make it possible to capture the quantitative details of a biochemical reaction network. We implemented SBGNtext2BioPEPA, a tool that demonstrates how such quantitative details can be used to automatically generate working Bio-PEPA code from a textual representation of SBGN-PD that we developed. Bio-PEPA is a process algebra that was designed for implementing quantitative models of concurrent biochemical reaction systems. We use this approach to compute the expected delay between input and output using deterministic and stochastic simulations of the MAPK signal transduction cascade. The scheme developed here is general and can be easily adapted to other output formalisms

High Deleterious Genomic Mutation Rate in Stationary Phase of Escherichia coli

In natural habitats, bacteria spend most of their time in some form of growth arrest. Little is known about deleterious mutations in such stages, and consequently there is limited understanding of what evolutionary events occur. In a deleterious mutation accumulation experiment in prolonged stationary phase of Escherichia coli, about 0.03 slightly deleterious mutations were observed per genome per day. This is over an order of magnitude higher than extrapolations from fast-growing cells, but in line with inferences from observations in adaptive stationary phase mutation experiments. These findings may affect understanding of bacterial evolution and the emergence of bacterial pathogenicity

Complementary approaches to understanding the plant circadian clock

Circadian clocks are oscillatory genetic networks that help organisms adapt to the 24-hour day/night cycle. The clock of the green alga Ostreococcus tauri is the simplest plant clock discovered so far. Its many advantages as an experimental system facilitate the testing of computational predictions. We present a model of the Ostreococcus clock in the stochastic process algebra Bio-PEPA and exploit its mapping to different analysis techniques, such as ordinary differential equations, stochastic simulation algorithms and model-checking. The small number of molecules reported for this system tests the limits of the continuous approximation underlying differential equations. We investigate the difference between continuous-deterministic and discrete-stochastic approaches. Stochastic simulation and model-checking allow us to formulate new hypotheses on the system behaviour, such as the presence of self-sustained oscillations in single cells under constant light conditions. We investigate how to model the timing of dawn and dusk in the context of model-checking, which we use to compute how the probability distributions of key biochemical species change over time. These show that the relative variation in expression level is smallest at the time of peak expression, making peak time an optimal experimental phase marker. Building on these analyses, we use approaches from evolutionary systems biology to investigate how changes in the rate of mRNA degradation impacts the phase of a key protein likely to affect fitness. We explore how robust this circadian clock is towards such potential mutational changes in its underlying biochemistry. Our work shows that multiple approaches lead to a more complete understanding of the clock

Quantitative genome re-sequencing defines multiple mutations conferring chloroquine resistance in rodent malaria

<p>Abstract</p> <p>Background</p> <p>Drug resistance in the malaria parasite <it>Plasmodium falciparum </it>severely compromises the treatment and control of malaria. A knowledge of the critical mutations conferring resistance to particular drugs is important in understanding modes of drug action and mechanisms of resistances. They are required to design better therapies and limit drug resistance.</p> <p>A mutation in the gene (<it>pfcrt</it>) encoding a membrane transporter has been identified as a principal determinant of chloroquine resistance in <it>P</it>. <it>falciparum</it>, but we lack a full account of higher level chloroquine resistance. Furthermore, the determinants of resistance in the other major human malaria parasite, <it>P. vivax</it>, are not known. To address these questions, we investigated the genetic basis of chloroquine resistance in an isogenic lineage of rodent malaria parasite <it>P. chabaudi </it>in which high level resistance to chloroquine has been progressively selected under laboratory conditions.</p> <p>Results</p> <p>Loci containing the critical genes were mapped by Linkage Group Selection, using a genetic cross between the high-level chloroquine-resistant mutant and a genetically distinct sensitive strain. A novel high-resolution quantitative whole-genome re-sequencing approach was used to reveal three regions of selection on chr11, chr03 and chr02 that appear progressively at increasing drug doses on three chromosomes. Whole-genome sequencing of the chloroquine-resistant parent identified just four point mutations in different genes on these chromosomes. Three mutations are located at the foci of the selection valleys and are therefore predicted to confer different levels of chloroquine resistance. The critical mutation conferring the first level of chloroquine resistance is found in <it>aat1</it>, a putative aminoacid transporter.</p> <p>Conclusions</p> <p>Quantitative trait loci conferring selectable phenotypes, such as drug resistance, can be mapped directly using progressive genome-wide linkage group selection. Quantitative genome-wide short-read genome resequencing can be used to reveal these signatures of drug selection at high resolution. The identities of three genes (and mutations within them) conferring different levels of chloroquine resistance generate insights regarding the genetic architecture and mechanisms of resistance to chloroquine and other drugs. Importantly, their orthologues may now be evaluated for critical or accessory roles in chloroquine resistance in human malarias <it>P. vivax </it>and <it>P. falciparum</it>.</p

Experimental evolution, genetic analysis and genome re-sequencing reveal the mutation conferring artemisinin resistance in an isogenic lineage of malaria parasites

<p>Abstract</p> <p>Background</p> <p>Classical and quantitative linkage analyses of genetic crosses have traditionally been used to map genes of interest, such as those conferring chloroquine or quinine resistance in malaria parasites. Next-generation sequencing technologies now present the possibility of determining genome-wide genetic variation at single base-pair resolution. Here, we combine <it>in vivo </it>experimental evolution, a rapid genetic strategy and whole genome re-sequencing to identify the precise genetic basis of artemisinin resistance in a lineage of the rodent malaria parasite, <it>Plasmodium chabaudi</it>. Such genetic markers will further the investigation of resistance and its control in natural infections of the human malaria, <it>P. falciparum</it>.</p> <p>Results</p> <p>A lineage of isogenic <it>in vivo </it>drug-selected mutant <it>P. chabaudi </it>parasites was investigated. By measuring the artemisinin responses of these clones, the appearance of an <it>in vivo </it>artemisinin resistance phenotype within the lineage was defined. The underlying genetic locus was mapped to a region of chromosome 2 by Linkage Group Selection in two different genetic crosses. Whole-genome deep coverage short-read re-sequencing (Illumina^®Solexa) defined the point mutations, insertions, deletions and copy-number variations arising in the lineage. Eight point mutations arise within the mutant lineage, only one of which appears on chromosome 2. This missense mutation arises contemporaneously with artemisinin resistance and maps to a gene encoding a de-ubiquitinating enzyme.</p> <p>Conclusions</p> <p>This integrated approach facilitates the rapid identification of mutations conferring selectable phenotypes, without prior knowledge of biological and molecular mechanisms. For malaria, this model can identify candidate genes before resistant parasites are commonly observed in natural human malaria populations.</p

Standing together for reproducibility in large-scale computing: report on reproducibility@XSEDE

This is the final report on reproducibility@xsede, a one-day workshop held in conjunction with XSEDE14, the annual conference of the Extreme Science and Engineering Discovery Environment (XSEDE). The workshop's discussion-oriented agenda focused on reproducibility in large-scale computational research. Two important themes capture the spirit of the workshop submissions and discussions: (1) organizational stakeholders, especially supercomputer centers, are in a unique position to promote, enable, and support reproducible research; and (2) individual researchers should conduct each experiment as though someone will replicate that experiment. Participants documented numerous issues, questions, technologies, practices, and potentially promising initiatives emerging from the discussion, but also highlighted four areas of particular interest to XSEDE: (1) documentation and training that promotes reproducible research; (2) system-level tools that provide build- and run-time information at the level of the individual job; (3) the need to model best practices in research collaborations involving XSEDE staff; and (4) continued work on gateways and related technologies. In addition, an intriguing question emerged from the day's interactions: would there be value in establishing an annual award for excellence in reproducible research? Overvie