New directions in kinetic high information content assays

Graphical approach to model reduction for nonlinear biochemical networks

Model reduction is a central challenge to the development and analysis of multiscale physiology models. Advances in model reduction are needed not only for computational feasibility but also for obtaining conceptual insights from complex systems. Here, we introduce an intuitive graphical approach to model reduction based on phase plane analysis. Timescale separation is identified by the degree of hysteresis observed in phase-loops, which guides a “concentration-clamp” procedure for estimating explicit algebraic relationships between species equilibrating on fast timescales. The primary advantages of this approach over Jacobian-based timescale decomposition are that: 1) it incorporates nonlinear system dynamics, and 2) it can be easily visualized, even directly from experimental data. We tested this graphical model reduction approach using a 25-variable model of cardiac β₁-adrenergic signaling, obtaining 6- and 4-variable reduced models that retain good predictive capabilities even in response to new perturbations. These 6 signaling species appear to be optimal “kinetic biomarkers” of the overall β₁-adrenergic pathway. The 6-variable reduced model is well suited for integration into multiscale models of heart function, and more generally, this graphical model reduction approach is readily applicable to a variety of other complex biological systems.

Translocation Biosensors - Cellular System Integrators to Dissect CRM1-Dependent Nuclear Export by Chemicogenomics

Fluorescent protein biosensors are powerful cellular systems biology tools for dissecting the complexity of cellular processes with high spatial and temporal resolution. As regulated nucleo-cytoplasmic transport is crucial for the modulation of numerous (patho)physiological cellular responses, a detailed understanding of its molecular mechanism would open up novel options for a rational manipulation of the cell. In contrast to genetic approaches, we here established and employed high-content cellular translocation biosensors applicable for dissecting nuclear export by chemicogenomics. A431 cell lines, stably expressing a translocation biosensor composed of glutathione S-transferase, GFP and a rational combination of nuclear import and export signals, were engineered by antibiotic selection and flow cytometry sorting. Using an optimized nuclear translocation algorithm, the translocation response could be robustly quantified on the Cellomics Arrayscan^® VTI platform. Subsequent to assay optimization, the assay was developed into a higher density 384-well format high-content assay and employed for the screening of the 17K ChemBioNet compound collection. This library was selected on the basis of a genetic algorithm used to identify maximum common chemical substructures in a database of annotated bioactive molecules and hence, is well-placed in the chemical space covered by bioactive compounds. Automated multiparameter data analysis combined with visual inspection allowed us to identify and to rationally discriminate true export inhibitors from false positives, which included fluorescent compounds or cytotoxic substances that dramatically affected the cellular morphology. A total of 120 potential hit compounds were selected for Cellomics Arrayscan^® VTI based rescreening. The export inhibitory activity of 20 compounds effective at concentrations < 25 μM were confirmed by fluorescence microscopy in several cell lines. Interestingly, kinetic analysis allowed the identification of inhibitors capable to interfere with the export receptor CRM1-mediated nuclear export not only in an irreversible, but also in a reversible fashion. In sum, exploitation of biosensor based screening allows the identification of chemicogenomic tools applicable for dissecting nucleo-cytoplasmic transport in living cells.

Integrating multi-unit electrophysiology and plastic culture dishes for network neuroscience

The electrophysiological characterisation of cultured neurons is of paramount importance for drug discovery, safety pharmacology and basic research in the neurosciences. Technologies offering low cost, low technical complexity and potential for scalability towards high-throughput electrophysiology on in vitro neurons would be advantageous, in particular for screening purposes. Here we describe a plastic culture substrate supporting low-complexity multi-unit loose-patch recording and stimulation of developing networks while retaining manufacturability compatible with low-cost and large-scale production. Our hybrid polydimethylsilane (PDMS)-on-polystyrene structures include chambers (6 mm in diameter) and microchannels (25 microm x 3.7 microm x 1 mm) serving as substrate-embedded recording pipettes. Somas are plated and retained in the chambers due to geometrical constraints and their processes grow along the microchannels, effectively establishing a loose-patch configuration without human intervention. We demonstrate that off-the-shelf voltage-clamp, current-clamp and extracellular amplifiers can be used to record and stimulate multi-unit activity with the aid of our dishes. Spikes up to 50 pA in voltage-clamp and 300 microV in current-clamp modes are recorded in sparse and bursting activity patterns characteristic of 1 week-old hippocampal cultures. Moreover, spike sorting employing principal component analysis (PCA) confirms that single microchannels support the recording of multiple neurons. Overall, this work suggests a strategy to endow conventional culture plasticware with added functionality to enable cost-efficient network electrophysiology.

Strategies for label-free optical detection

A large number of methods using direct detection with label-free systems are known. They compete with the well-introduced fluorescence-based methods. However, recent applications take advantage of label-free detection in protein-protein interactions, high-throughput screening, and high-content screening. These new applications require new strategies for biosensors. It becomes more and more obvious that neither the transduction principle nor the recognition elements for the biomolecular interaction process alone determine the quality of the biosensor. Accordingly, the biosensor system has to be considered as a whole. This chapter focuses on strategies to optimize the detection platform and the biomolecular recognition layer. It concentrates on direct detection methods, with special focus on optical transduction. Since even this restriction still leaves a large number of methods, only microrefractometric and microreflectometric methods using planar transducers have been selected for a detailed description and a listing of applications. However, since many review articles on the physical principles exist, the description is kept short. Other methods are just mentioned in brief and for comparison. The outlook and the applications demonstrate the future perspectives of direct optical detection in bioanalytics.