The molecular complexity within a cell may be seen as an evolutionary response to the external complexity of the cell's environment. This suggests that the external environment may be harnessed to interrogate the cell's internal molecular architecture. Cells, however, are not only nonlinear and non-stationary, but also exhibit heterogeneous responses within a clonal, isogenic population. In effect, each cell undertakes its own experiment. Here, we develop a method of cellular interrogation using programmable microfluidic devices which exploits the additional information present in cell-to-cell variation, without requiring model parameters to be fitted to data. We focussed on Ca2+ signalling in response to hormone stimulation, which exhibits oscillatory spiking in many cell types and chose eight models of Ca2+ signalling networks which exhibit similar behaviour in simulation. We developed a nonlinear frequency analysis for non-stationary responses, which could classify models into groups under parameter variation, but found that this question alone was unable to distinguish critical feedback loops. We further developed a nonlinear amplitude analysis and found that the combination of both questions ruled out six of the models as inconsistent with the experimentally-observed dynamics and heterogeneity. The two models that survived the double interrogation were mathematically different but schematically identical and yielded the same unexpected predictions that we confirmed experimentally. Further analysis showed that subtle mathematical details can markedly influence non-stationary responses under parameter variation, emphasising the difficulty of finding a "correct" model. By developing questions for the pathway being studied, and designing more versatile microfluidics, cellular interrogation holds promise as a systematic strategy that can complement direct intervention by genetics or pharmacology.

SUMMARY: Molecular networks are often studied in diverse cellular or experimental contexts, with highly context-specific details. Modelling introduces further choices as to levels of mathematical description. The resulting possibilities are difficult to explore rapidly, hampering the integration of modelling and experiment. We have developed Proteus, a web-based, context-specific tool for building compartmentalized, ordinary differential equation (ODE) models. It is inspired by the idea of a molecular 'toolkit' for Ca(2+) signalling. Toolkits in Proteus are context-independent representations of biological systems as sets of components, which may correspond to mechanisms of differing levels of complexity. Users pick and choose components from a toolkit and, for each component, pick and choose from different mechanisms, each of which describes a different instantiation of the component's mechanism. Proteus combines these choices into a system of ODEs, which may then be downloaded in SBML (Systems Biology Markup Language), Matlab or Fortran format and independently analyzed. Toolkits, components and mechanisms are user-constructible, either de novo or by cannibalizing existing models, including all those in the Biomodels database. A wide variety of context-specific models may thereby be rapidly built, modified and explored. AVAILABILITY AND IMPLEMENTATION: Proteus, implemented in C#, and a prototype toolkit for modelling calcium signalling are freely and universally available at www.modularmodeling.com CONTACT: [email protected]; [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOTIVATION: Lysine acetylation is a post-translational protein modification and a primary regulatory mechanism that controls many cell signaling processes. Lysine acetylation sites are recognized by acetyltransferases and deacetylases through sequence patterns (motifs). Recently, we used high-resolution mass spectrometry to identify 3600 lysine acetylation sites on 1750 human proteins covering most of the previously annotated sites and providing the most comprehensive acetylome so far. This dataset should provide an excellent source to train support vector machines (SVMs) allowing the high accuracy in silico prediction of acetylated lysine residues. RESULTS: We developed a SVM to predict acetylated residues. The precision of our acetylation site predictor is 78% at 78% recall on input data containing equal numbers of modified and non-modified residues. AVAILABILITY: The online predictor is available at http://www.phosida.com CONTACT: [email protected]

UNLABELLED: We describe Sebida, a database of genes with sex-biased expression. The database integrates results from multiple, independent microarray studies comparing male and female gene expression in Drosophila melanogaster, Drosophila simulans and Anopheles gambiae. Sebida uses standard nomenclature, which allows individual genes to be compared across different microarray platforms and to be queried by gene name, symbol, or annotation number. In addition to ratios of male/female expression for each gene, Sebida also contains information useful for evolutionary studies, such as local recombination rate, degree of codon bias and interspecific divergence at synonymous and non-synonymous sites. AVAILABILITY: Sebida can be accessed at http://www.sebida.de