Live-cell Imaging of Single-Cell Arrays (LISCA) - a Versatile Technique to Quantify Cellular Kinetics.

Live-cell Imaging of Single-Cell Arrays (LISCA) is a versatile method to collect time courses of fluorescence signals from individual cells in high throughput. In general, the acquisition of single-cell time courses from cultured cells is hampered by cell motility and diversity of cell shapes. Adhesive micro-arrays standardize single-cell conditions and facilitate image analysis. LISCA combines single-cell microarrays with scanning time-lapse microscopy and automated image processing. Here, we describe the experimental steps of taking single-cell fluorescence time courses in a LISCA format. We transfect cells adherent to a micropatterned array using mRNA encoding for enhanced green fluorescent protein (eGFP) and monitor the eGFP expression kinetics of hundreds of cells in parallel via scanning time-lapse microscopy. The image data stacks are automatically processed by newly developed software that integrates fluorescence intensity over selected cell contours to generate single-cell fluorescence time courses. We demonstrate that eGFP expression time courses after mRNA transfection are well described by a simple kinetic translation model that reveals expression and degradation rates of mRNA. Further applications of LISCA for event time correlations of multiple markers in the context of signaling apoptosis are discussed.

Erratum: Publisher Correction: Multi-experiment nonlinear mixed effect modeling of single-cell translation kinetics after transfection.

[This corrects the article DOI: 10.1038/s41540-018-0079-7.].

Multi-experiment nonlinear mixed effect modeling of single-cell translation kinetics after transfection.

Single-cell time-lapse studies have advanced the quantitative understanding of cellular pathways and their inherent cell-to-cell variability. However, parameters retrieved from individual experiments are model dependent and their estimation is limited, if based on solely one kind of experiment. Hence, methods to integrate data collected under different conditions are expected to improve model validation and information content. Here we present a multi-experiment nonlinear mixed effect modeling approach for mechanistic pathway models, which allows the integration of multiple single-cell perturbation experiments. We apply this approach to the translation of green fluorescent protein after transfection using a massively parallel read-out of micropatterned single-cell arrays. We demonstrate that the integration of data from perturbation experiments allows the robust reconstruction of cell-to-cell variability, i.e., parameter densities, while each individual experiment provides insufficient information. Indeed, we show that the integration of the datasets on the population level also improves the estimates for individual cells by breaking symmetries, although each of them is only measured in one experiment. Moreover, we confirmed that the suggested approach is robust with respect to batch effects across experimental replicates and can provide mechanistic insights into the nature of batch effects. We anticipate that the proposed multi-experiment nonlinear mixed effect modeling approach will serve as a basis for the analysis of cellular heterogeneity in single-cell dynamics.

Single Cell Microarrays Fabricated by Microscale Plasma-Initiated Protein Patterning (µPIPP).

Micropatterned arrays considerably advanced single cell fluorescence time-lapse measurements by providing standardized boundary conditions for thousands of cells in parallel. In these assays, cells are forced to adhere to defined microstructured protein islands separated by passivated, nonadhesive areas. Here we provide a detailed protocol on how to reproducibly fabricate high quality single cell arrays by microscale plasma-initiated protein patterning (µPIPP). Advantages of µPIPP arrays are the ease of preparation and the unrestricted choice of substrates as well as proteins. We demonstrate how the arrays enable the efficient measurement of single cell time trajectories using automated data acquisition and data analysis by example of single cell gene expression after mRNA transfection and time courses of single cell apoptosis. We discuss the more general use of the protocol for assessment of single cell dynamics with the help of fluorescent reporters.

Versatile method to generate multiple types of micropatterns.

Micropatterning techniques have become an important tool for the study of cell behavior in controlled microenvironments. As a consequence, several approaches for the creation of micropatterns have been developed in recent years. However, the diversity of substrates, coatings, and complex patterns used in cell science is so great that no single existing technique is capable of fabricating designs suitable for all experimental conditions. Hence, there is a need for patterning protocols that are flexible with regard to the materials used and compatible with different patterning strategies to create more elaborate setups. In this work, the authors present a versatile approach to micropatterning. The protocol is based on plasma treatment, protein coating, and a poly(L-lysine)-grafted-poly(ethylene glycol) backfill step, and produces homogeneous patterns on a variety of substrates. Protein density within the patterns can be controlled, and density gradients of surface-bound protein can be formed. Moreover, by combining the method with microcontact printing, it is possible to generate patterns composed of three different components within one iteration of the protocol. The technique is simple to implement and should enable cell science labs to create a broad range of complex and highly specialized microenvironments.

Arraying cell cultures using PEG-DMA micromolding in standard culture dishes.

A robust and effortless procedure is presented, which allows for the microstructuring of standard cell culture dishes. Cell adhesion and proliferation are controlled by three-dimensional poly(ethylene glycol)-dimethacrylate (PEG-DMA) microstructures. The spacing between microwells can be extended to millimeter size in order to enable the combination with robotic workstations. Cell arrays of microcolonies can be studied under boundary-free growth conditions by lift-off of the PEG-DMA layer in which the growth rate is accessible via the evolution of patch areas. Alternatively, PEG-DMA stencils can be used as templates for plasma-induced patterning.