ASPASIA: A toolkit for evaluating the effects of biological interventions on SBML model behavior

<div><p>A calibrated computational model reflects behaviours that are expected or observed in a complex system, providing a baseline upon which sensitivity analysis techniques can be used to analyse pathways that may impact model responses. However, calibration of a model where a behaviour depends on an intervention introduced after a defined time point is difficult, as model responses may be dependent on the conditions at the time the intervention is applied. We present ASPASIA (Automated Simulation Parameter Alteration and SensItivity Analysis), a cross-platform, open-source Java toolkit that addresses a key deficiency in software tools for understanding the impact an intervention has on system behaviour for models specified in Systems Biology Markup Language (SBML). ASPASIA can generate and modify models using SBML solver output as an initial parameter set, allowing interventions to be applied once a steady state has been reached. Additionally, multiple SBML models can be generated where a subset of parameter values are perturbed using local and global sensitivity analysis techniques, revealing the model’s sensitivity to the intervention. To illustrate the capabilities of ASPASIA, we demonstrate how this tool has generated novel hypotheses regarding the mechanisms by which Th17-cell plasticity may be controlled <i>in vivo</i>. By using ASPASIA in conjunction with an SBML model of Th17-cell polarisation, we predict that promotion of the Th1-associated transcription factor T-bet, rather than inhibition of the Th17-associated transcription factor ROR<i>γ</i>t, is sufficient to drive switching of Th17 cells towards an IFN-<i>γ</i>-producing phenotype. Our approach can be applied to all SBML-encoded models to predict the effect that intervention strategies have on system behaviour. ASPASIA, released under the Artistic License (2.0), can be downloaded from <a href="http://www.york.ac.uk/ycil/software" target="_blank">http://www.york.ac.uk/ycil/software</a>.</p></div

Shouldn't enantiomeric purity be included in the minimum information about a bioactive entity? Response from the MIABE group

[Reply to Letter

RA-MAP, molecular immunological landscapes in early rheumatoid arthritis and healthy vaccine recipients

Rheumatoid arthritis (RA) is a chronic inflammatory disorder with poorly defined aetiology characterised by synovial inflammation with variable disease severity and drug responsiveness. To investigate the peripheral blood immune cell landscape of early, drug naive RA, we performed comprehensive clinical and molecular profiling of 267 RA patients and 52 healthy vaccine recipients for up to 18 months to establish a high quality sample biobank including plasma, serum, peripheral blood cells, urine, genomic DNA, RNA from whole blood, lymphocyte and monocyte subsets. We have performed extensive multi-omic immune phenotyping, including genomic, metabolomic, proteomic, transcriptomic and autoantibody profiling. We anticipate that these detailed clinical and molecular data will serve as a fundamental resource offering insights into immune-mediated disease pathogenesis, progression and therapeutic response, ultimately contributing to the development and application of targeted therapies for RA.</p

A computational framework for complex disease stratification from multiple large-scale datasets.

BACKGROUND: Multilevel data integration is becoming a major area of research in systems biology. Within this area, multi-'omics datasets on complex diseases are becoming more readily available and there is a need to set standards and good practices for integrated analysis of biological, clinical and environmental data. We present a framework to plan and generate single and multi-'omics signatures of disease states. METHODS: The framework is divided into four major steps: dataset subsetting, feature filtering, 'omics-based clustering and biomarker identification. RESULTS: We illustrate the usefulness of this framework by identifying potential patient clusters based on integrated multi-'omics signatures in a publicly available ovarian cystadenocarcinoma dataset. The analysis generated a higher number of stable and clinically relevant clusters than previously reported, and enabled the generation of predictive models of patient outcomes. CONCLUSIONS: This framework will help health researchers plan and perform multi-'omics big data analyses to generate hypotheses and make sense of their rich, diverse and ever growing datasets, to enable implementation of translational P4 medicine

Isolation and Characterisation of Four Cathepsin B-Like Cysteine Protease Genes From the Free Living Nematode Caenorhabditis elegans

The cathepsin B cysteine protease enzyme performs a role in protein turnover and degradation within the lysosomes of vertebrates. This proteolytic enzyme is also thought to perform related roles in the processing of antigens and protein precursors, as well as a role in bone resorption. A pathological role for cathepsin B in tumour cell invasion has also been suggested. Enzymes with cathepsin B-like activities are thought to be excreted and/or secreted by a variety of parasitic nematode and trematode species. To date, multigene families with the potential to encode cathepsin B-like enzymes have only been reported in parasitic nematode and trematode species, suggesting that these enzymes may be important for parasitism by these species. The work presented in this thesis demonstrates that the free living nematode species, Caenorhabditis elegans, also possesses a cathepsin B-like multigene family indicating that such multigene families are not unique to parasitic nematode and trematode species. Four genes with homology to vertebrate cathepsin B were isolated from the genome of C. elegans and were named cpr-3, cpr-4, cpr-5 and cpr-6. Phylogenetic analysis clusters the proteins encoded by these four genes with known cathepsin B enzymes and away from other, related enzymes such as cathepsins H and L. Since the four genes possess distinct genomic architectures, they appear to have arisen from ancient gene duplication events. This is supported by phylogenetic analysis which clusters the predicted proteins encoded by these four genes and cpr-1, a previously isolated C.elegans cathepsin B-like gene (Ray and McKerrow, 1991), into three groups which are almost as diverged from one another as each is to the vertebrate cathepsin B enzymes. The expression of cpr-3, cpr-4, cpr-5 and cpr-6 as lacZ reporter transgene fusions in transgenic worms suggests that these four genes are all exclusively expressed in the intestinal cells of C. elegans. Analysis of the temporal expression patterns of these four genes using semi-quantitative reverse transcription polymerase chain reaction indicates that the four genes exhibit distinct but overlapping temporal patterns of expression during C. elegans development. These results suggest a differential requirement for cathepsin B-like enzymes, or combinations of enzymes, within the intestine during C. elegans development

Isolation and characterization of four developmentally regulated cathepsin B-like cysteine protease genes from the nematode Caenorhabditis elegans

Cathepsin B cysteine protease enzymes have been shown to be involved in a variety of different biological processes in eukaryotes. We have isolated and characterized four distinct cathepsin B-like genes from the genetically tractable nematode, Caenorhabditis elegans. This is the first reported finding of a cathepsin B-like multigene family within a nonparasitic metazoan. The four genes possess distinct genomic architectures, with variations in the position, number, and size of introns. The predicted amino acid sequences of the four genes are highly diverged. Phylogenetic analysis indicates the divergence of this multigene family within C. elegans is as great as the interspecies divergence between the vertebrates and nematode cathepsin B-like genes. In addition, each of the four genes described here shows a distinct temporal pattern of expression during C. elegans development

Systems Research 3-2104.2B

In recent years significant progress has been made in ou