Bacterial transmembrane signalling systems and their engineering for biosensing

Every living cell possesses numerous transmembrane signalling systems that receive chemical and physical stimuli from the environment and transduce this information into an intracellular signal that triggers some form of cellular response. As unicellular organisms, bacteria require these systems for survival in rapidly changing environments. The receptors themselves act as ‘sensory organs’, while subsequent signalling circuits can be regarded as forming a ‘neural network’ that is involved in decision making, adaptation and ultimately in ensuring survival. Bacteria serve as useful biosensors in industry and clinical diagnostics, in addition to producing drugs for therapeutic purposes. Therefore, there is a great demand for engineered bacterial strains that contain transmembrane signalling systems with high molecular specificity, sensitivity and dose dependency. In this review, we address the complexity of transmembrane signalling systems and discuss principles to rewire receptors and their signalling outputs.

Visualization of ligand-induced transmembrane signalling in the full-length human insulin receptor

ABSTRACTUsing glycosylated full-length human insulin receptor reconstituted into lipid nanodiscs, we show that insulin binding to the dimeric receptor converts its ectodomains from an inverted U-shaped to a T-shaped conformation. This unprecedented structural rearrangement of the ectodomains propagates to the transmembrane domains, which are well separated in the inactive conformation, but come together upon insulin binding, allowing autophosphorylation of the cytoplasmic kinase domains.

QuimP – Analyzing transmembrane signalling in highly deformable cells

SummaryTransmembrane signalling plays important physiological roles, with G protein–coupled cell surface receptors being particularly important therapeutic targets. Fluorescent proteins are widely used to study signalling, but the analysis of image time series can be challenging, in particular when changes in cell shape are involved. To this end we have developed QuimP software. QuimP semi-automatically tracks cell outlines, quantifies spatio-temporal patterns of fluorescence at the cell membrane, and tracks local shape deformations. QuimP is particularly useful for studying cell motility, for example in immune or cancer cells.Availability and ImplementationQuimP (http://warwick.ac.uk/quimp) consists of a set of Java plugins for Fiji/ImageJ (http://fiji.sc/) and can be easily installed through the Fiji Updater (http://warwick.ac.uk/quimp/wiki-pages/installation). It is compatible with Mac, Windows and Unix-based operating systems, requiring version >1.45 of Fiji/ImageJ and Java 8. QuimP is released as open source (https://github.com/CellDynamics/QuimP/) under an academic [email protected] InformationSupplementary materials (SI-A to SI-D) are available at Bioinformatics online. Test data is available from http://warwick.ac.uk/quimp/test_data.