Imaging proprotein convertase activities and their regulation in the implanting mouse blastocyst

The CLIP biosensor reveals the spatiotemporal activity of the Nodal proprotein convertases Furin and Pace4 during embryonic development

Automated microscopy for high-content RNAi screening

Fluorescence microscopy is one of the most powerful tools to investigate complex cellular processes such as cell division, cell motility, or intracellular trafficking. The availability of RNA interference (RNAi) technology and automated microscopy has opened the possibility to perform cellular imaging in functional genomics and other large-scale applications. Although imaging often dramatically increases the content of a screening assay, it poses new challenges to achieve accurate quantitative annotation and therefore needs to be carefully adjusted to the specific needs of individual screening applications. In this review, we discuss principles of assay design, large-scale RNAi, microscope automation, and computational data analysis. We highlight strategies for imaging-based RNAi screening adapted to different library and assay designs

Design Strategies of Fluorescent Biosensors Based on Biological Macromolecular Receptors

Fluorescent biosensors to detect the bona fide events of biologically important molecules in living cells are increasingly demanded in the field of molecular cell biology. Recent advances in the development of fluorescent biosensors have made an outstanding contribution to elucidating not only the roles of individual biomolecules, but also the dynamic intracellular relationships between these molecules. However, rational design strategies of fluorescent biosensors are not as mature as they look. An insatiable request for the establishment of a more universal and versatile strategy continues to provide an attractive alternative, so-called modular strategy, which permits facile preparation of biosensors with tailored characteristics by a simple combination of a receptor and a signal transducer. This review describes an overview of the progress in design strategies of fluorescent biosensors, such as auto-fluorescent protein-based biosensors, protein-based biosensors covalently modified with synthetic fluorophores, and signaling aptamers, and highlights the insight into how a given receptor is converted to a fluorescent biosensor. Furthermore, we will demonstrate a significance of the modular strategy for the sensor design

Optical Control of Ligand-Gated Ion Channels

In the vibrant field of optogenetics, optics and genetic targeting are combined to commandeer cellular functions, such as the neuronal action potential, by optically stimulating light-sensitive ion channels expressed in the cell membrane. One broadly applicable manifestation of this approach are covalently attached photochromic tethered ligands (PTLs) that allow activating ligand-gated ion channels with outstanding spatial and temporal resolution. Here, we describe all steps towards the successful development and application of PTL-gated ion channels in cell lines and primary cells. The basis for these experiments forms a combination of molecular modeling, genetic engineering, cell culture, and electrophysiology. The light-gated glutamate receptor (LiGluR), which consists of the PTL-functionalized GluK2 receptor, serves as a model

Fluctuation Analysis of Activity Biosensor Images for the Study of Information Flow in Signaling Pathways

Comprehensive understanding of cellular signal transduction requires accurate measurement of the information flow in molecular pathways. In the past, information flow has been inferred primarily from genetic or protein-protein interactions. Although useful for overall signaling, these approaches are limited in that they typically average over populations of cells. Single cell data of signaling states are emerging, but these data are usually snapshots of a particular time point or limited to averaging over a whole cell. However, many signaling pathways are activated only transiently in specific subcellular regions. Protein activity biosensors allow measurement of the spatiotemporal activation of signaling molecules in living cells. These data contain highly complex, dynamic information that can be parsed out in time and space and compared with other signaling events as well as changes in cell structure and morphology. We describe in this chapter the use of computational tools to correct, extract, and process information from timelapse images of biosensors. These computational tools allow one to explore the biosensor signals in a multiplexed approach in order to reconstruct the sequence of signaling events and consequently the topology of the underlying pathway. The extraction of this information, dynamics and topology, provides insight into how the inputs of a signaling network are translated into its biochemical or mechanical outputs