TIMING 2.0: High-throughput single-cell profiling of dynamic cell-cell interactions by time-lapse imaging microscopy in nanowell grids (original) (raw)
Related papers
Bioimage informatics, 2018
Motivation: Automated profiling of cell-cell interactions from high-throughput time-lapse imaging microscopy data of cells in nanowell grids (TIMING) has led to fundamental insights into cell-cell interactions in immunotherapy. This application note aims to enable widespread adoption of TIMING by (i) enabling the computations to occur on a desktop computer with a graphical processing unit instead of a server; (ii) enabling image acquisition and analysis to occur in the laboratory avoiding network data transfers to/from a server and (iii) providing a comprehensive graphical user interface. Results: On a desktop computer, TIMING 2.0 takes 5 s/block/image frame, four times faster than our previous method on the same computer, and twice as fast as our previous method (TIMING) running on a Dell PowerEdge server. The cell segmentation accuracy (f-number = 0.993) is superior to our previous method (f-number ¼ 0.821). A graphical user interface provides the ability to inspect the video analysis results, make corrective edits efficiently (one-click editing of an entire nanowell video sequence in 5-10 s) and display a summary of the cell killing efficacy measurements. Availability and implementation: Open source Python software (GPL v3 license), instruction manual , sample data and sample results are included with the Supplement (https://github.com/ RoysamLab/TIMING2).
Scientific Reports, 2019
Cell-cell interactions are an observable manifestation of underlying complex biological processes occurring in response to diversified biochemical stimuli. Recent experiments with microfluidic devices and live cell imaging show that it is possible to characterize cell kinematics via computerized algorithms and unravel the effects of targeted therapies. We study the influence of spatial and temporal resolutions of time-lapse videos on motility and interaction descriptors with computational models that mimic the interaction dynamics among cells. We show that the experimental set-up of time-lapse microscopy has a direct impact on the cell tracking algorithm and on the derived numerical descriptors. We also show that, when comparing kinematic descriptors in two diverse experimental conditions, too low resolutions may alter the descriptors’ discriminative power, and so the statistical significance of the difference between the two compared distributions. The conclusions derived from the ...
ACDC: Automated Cell Detection and Counting for Time-lapse Fluorescence Microscopy
Advances in microscopy imaging technologies have enabled the visualization of live-cell dynamic processes using time-lapse microscopy imaging. However, modern methods exhibit several limitations related to the training phases and to time constraints, hindering their application in the laboratory practice. In this work, we present a novel method, named Automated Cell Detection and Counting (ACDC), designed for activity detection of fluorescent labeled cell nuclei in time-lapse microscopy. ACDC overcomes the limitations of the literature methods, by first applying bilateral filtering on the original image to smooth the input cell images while preserving edge sharpness, and then by exploiting the watershed transform and morphological filtering. Moreover, ACDC represents a feasible solution for the laboratory practice, as it can leverage multi-core architectures in computer clusters to efficiently handle large-scale imaging datasets. Indeed, our Parent-Workers implementation of ACDC all...
Immunology and Cell Biology, 2013
We describe a new approach for interactive analysis of time-lapse microscopy, and apply this approach to elucidating whether polarity regulation is conserved between epithelial cells and lymphocytes. A key advantage of our analysis platform, 'TACTICS', is the capacity to visualize individual data points in the context of large data sets, similar to standard approaches in flow cytometry. Scatter plots representing microscopic parameters or their derivations such as polarity ratios are linked to the original data such that clicking on each dot enables a link to images and movies of the corresponding cell. Similar to flow cytometric analysis, subsets of the data can be gated and reanalyzed to explore the relationships between different parameters. TACTICS was used to dissect the regulation of polarization of the cell fate determinant, Numb, in migrating lymphocytes. We show here that residues of Numb that are phosphorylated by atypical protein kinase C (aPKC) to mediate apicobasal polarity in epithelial cells are not required for polarization of Numb in T cells, indicating that the role of aPKC is not conserved between lymphocytes and epithelia.
Nanocharacterization plays a vital role in understanding the complex nanoscale organization of cells and organelles. Understanding cellular function requires high-resolution information about how the cellular structures evolve over time. A number of techniques exist to resolve static nanoscale structure of cells in great detail (super-resolution optical microscopy, EM, AFM). However, time-resolved imaging techniques tend to either have a lower resolution, are limited to small areas, or cause damage to the cells, thereby preventing long-term time-lapse studies. Scanning probe microscopy methods such as atomic force microscopy (AFM) combine high-resolution imaging with the ability to image living cells in physiological conditions. The mechanical contact between the tip and the sample, however, deforms the cell surface, disturbs the native state, and prohibits long-term time-lapse imaging. Here, we develop a scanning ion conductance microscope (SICM) for high-speed and long-term nanoscale imaging of eukaryotic cells. By utilizing advances in nanopositioning, nanopore fabrication, microelectronics, and controls engineering, we developed a microscopy method that can resolve spatiotemporally diverse threedimensional (3D) processes on the cell membrane at sub-5-nm axial resolution. We tracked dynamic changes in live cell morphology with nanometer details and temporal ranges of subsecond to days, imaging diverse processes ranging from endocytosis, micropinocytosis, and mitosis to bacterial infection and cell differentiation in cancer cells. This technique enables a detailed look at membrane events and may offer insights into cell−cell interactions for infection, immunology, and cancer research.
Microfluidics-integrated time-lapse imaging for analysis of cellular dynamics
Integrative Biology, 2010
An understanding of the mechanisms regulating cellular responses has recently been augmented by innovations enabling the observation of phenotypes at high spatio-temporal resolution. Technologies such as microfluidics have sought to expand the throughput of these methods, although assimilation with advanced imaging strategies has been limited. Here, we describe the pairing of high resolution time-lapse imaging with microfluidic multiplexing for the analysis of cellular dynamics, utilizing a design selected for facile fabrication and operation, and integration with microscopy instrumentation. This modular, medium-throughput platform enables the long-term imaging of living cells at high numerical aperture (via oil immersion) by using a conserved 96-well, B6 Â 5 mm 2 imaging area with a variable input/output channel design chosen for the number of cell types and microenvironments under investigation. In the validation of this system, we examined fundamental features of cell cycle progression, including mitotic kinetics and spindle orientation dynamics, through the high-resolution parallel analysis of model cell lines subjected to anti-mitotic agents. We additionally explored the self-renewal kinetics of mouse embryonic stem cells, and demonstrate the ability to dynamically assess and manipulate stem cell proliferation, detect rare cell events, and measure extended timescale correlations. We achieved an experimental throughput of >900 cells/experiment, each observed at >40Â magnification for up to 120 h. Overall, these studies illustrate the capacity to probe cellular functions and yield dynamic information in time and space through the integration of a simple, modular, microfluidics-based imaging platform.
Strategies for implementing hardware-assisted high-throughput cellular image analysis
Journal of laboratory automation, 2011
Recent advances in imaging technology for biomedicine, including high-speed microscopy, automated microscopy, and imaging flow cytometry are poised to have a large impact on clinical diagnostics, drug discovery, and biological research. Enhanced acquisition speed, resolution, and automation of sample handling are enabling researchers to probe biological phenomena at an increasing rate and achieve intuitive image-based results. However, the rich image sets produced by these tools are massive, possessing potentially millions of frames with tremendous depth and complexity. As a result, the tools introduce immense computational requirements, and, more importantly, the fact that image analysis operates at a much lower speed than image acquisition limits its ability to play a role in critical tasks in biomedicine such as real-time decision making. In this work, we present our strategy for high-throughput image analysis on a graphical processing unit platform. We scrutinized our original a...
Data-analysis strategies for image-based cell profiling
Nature methods, 2017
Image-based cell profiling is a high-throughput strategy for the quantification of phenotypic differences among a variety of cell populations. It paves the way to studying biological systems on a large scale by using chemical and genetic perturbations. The general workflow for this technology involves image acquisition with high-throughput microscopy systems and subsequent image processing and analysis. Here, we introduce the steps required to create high-quality image-based (i.e., morphological) profiles from a collection of microscopy images. We recommend techniques that have proven useful in each stage of the data analysis process, on the basis of the experience of 20 laboratories worldwide that are refining their image-based cell-profiling methodologies in pursuit of biological discovery. The recommended techniques cover alternatives that may suit various biological goals, experimental designs, and laboratories' preferences.
Micropilot: automation of fluorescence microscopy–based imaging for systems biology
Nature Methods, 2011
Quantitative microscopy relies on imaging of large cell numbers but is often hampered by timeconsuming manual selection of specific cells. The 'Micropilot' software automatically detects cells of interest and launches complex imaging experiments including three-dimensional multicolor time-lapse or fluorescence recovery after photobleaching in live cells. In three independent experimental setups this allowed us to statistically analyze biological processes in detail and is thus a powerful tool for systems biology.