Enabling user-guided segmentation and tracking of surface-labeled cells in time-lapse image sets of living tissues

To study the process of morphogenesis, one often needs to collect and segment time-lapse images of living tissues to accurately track changing cellular morphology. This task typically involves segmenting and tracking tens to hundreds of individual cells over hundreds of image frames, a scale that would certainly benefit from automated routines; however, any automated routine would need to reliably handle a large number of sporadic, and yet typical problems (e.g., illumination inconsistency, photobleaching, rapid cell motions, and drift of focus or of cells moving through the imaging plane). Here, we present a segmentation and cell tracking approach based on the premise that users know their data best-interpreting and using image features that are not accounted for in any a priori algorithm design. We have developed a program, SeedWater Segmenter, that combines a parameter-less and fast automated watershed algorithm with a suite of manual intervention tools that enables users with little to no specialized knowledge of image processing to efficiently segment images with near-perfect accuracy based on simple user interactions.     

Measuring DNA content in live cells by fluorescence microscopy

Background

Live-cell fluorescence microscopy (LCFM) is a powerful tool used to investigate cellular dynamics in real time. However, the capacity to simultaneously measure DNA content in cells being tracked over time remains challenged by dye-associated toxicities. The ability to measure DNA content in single cells by means of LCFM would allow cellular stage and ploidy to be coupled with a variety of imaging directed analyses. Here we describe a widely applicable nontoxic approach for measuring DNA content in live cells by fluorescence microscopy. This method relies on introducing a live-cell membrane-permeant DNA fluorophore, such as Hoechst 33342, into the culture medium of cells at the end of any live-cell imaging experiment and measuring each cell’s integrated nuclear fluorescence to quantify DNA content. Importantly, our method overcomes the toxicity and induction of DNA damage typically caused by live-cell dyes through strategic timing of adding the dye to the cultures; allowing unperturbed cells to be imaged for any interval of time before quantifying their DNA content. We assess the performance of our method empirically and discuss adaptations that can be implemented using this technique.

Results

Presented in conjunction with cells expressing a histone 2B-GFP fusion protein (H2B-GFP), we demonstrated how this method enabled chromosomal segregation errors to be tracked in cells as they progressed through cellular division that were later identified as either diploid or polyploid. We also describe and provide an automated Matlab-derived algorithm that measures the integrated nuclear fluorescence in each cell and subsequently plots these measurements into a cell cycle histogram for each frame imaged. The algorithm’s accurate assessment of DNA content was validated by parallel flow cytometric studies.

Conclusions

This method allows the examination of single-cell dynamics to be correlated with cellular stage and ploidy in a high-throughput fashion. The approach is suitable for any standard epifluorescence microscope equipped with a stable illumination source and either a stage-top incubator or an enclosed live-cell incubation chamber. Collectively, we anticipate that this method will allow high-resolution microscopic analysis of cellular processes involving cell cycle progression, such as checkpoint activation, DNA replication, and cellular division.

     

Labour-Efficient In Vitro Lymphocyte Population Tracking and Fate Prediction Using Automation and Manual Review

Interest in cell heterogeneity and differentiation has recently led to increased use of time-lapse microscopy. Previous studies have shown that cell fate may be determined well in advance of the event. We used a mixture of automation and manual review of time-lapse live cell imaging to track the positions, contours, divisions, deaths and lineage of 44 B-lymphocyte founders and their 631 progeny in vitro over a period of 108 hours. Using this data to train a Support Vector Machine classifier, we were retrospectively able to predict the fates of individual lymphocytes with more than 90% accuracy, using only time-lapse imaging captured prior to mitosis or death of 90% of all cells. The motivation for this paper is to explore the impact of labour-efficient assistive software tools that allow larger and more ambitious live-cell time-lapse microscopy studies. After training on this data, we show that machine learning methods can be used for realtime prediction of individual cell fates. These techniques could lead to realtime cell culture segregation for purposes such as phenotype screening. We were able to produce a large volume of data with less effort than previously reported, due to the image processing, computer vision, tracking and human-computer interaction tools used. We describe the workflow of the software-assisted experiments and the graphical interfaces that were needed. To validate our results we used our methods to reproduce a variety of published data about lymphocyte populations and behaviour. We also make all our data publicly available, including a large quantity of lymphocyte spatio-temporal dynamics and related lineage information.     

Accumulative Difference Image Protocol for Particle Tracking in Fluorescence Microscopy Tested in Mouse Lymphonodes

The basic research in cell biology and in medical sciences makes large use of imaging tools mainly based on confocal fluorescence and, more recently, on non-linear excitation microscopy. Substantially the aim is the recognition of selected targets in the image and their tracking in time. We have developed a particle tracking algorithm optimized for low signal/noise images with a minimum set of requirements on the target size and with no a priori knowledge of the type of motion. The image segmentation, based on a combination of size sensitive filters, does not rely on edge detection and is tailored for targets acquired at low resolution as in most of the in-vivo studies. The particle tracking is performed by building, from a stack of Accumulative Difference Images, a single 2D image in which the motion of the whole set of the particles is coded in time by a color level. This algorithm, tested here on solid-lipid nanoparticles diffusing within cells and on lymphocytes diffusing in lymphonodes, appears to be particularly useful for the cellular and the in-vivo microscopy image processing in which few a priori assumption on the type, the extent and the variability of particle motions, can be done.     

A Parallel Distributed-Memory Particle Method Enables Acquisition-Rate Segmentation of Large Fluorescence Microscopy Images

Modern fluorescence microscopy modalities, such as light-sheet microscopy, are capable of acquiring large three-dimensional images at high data rate. This creates a bottleneck in computational processing and analysis of the acquired images, as the rate of acquisition outpaces the speed of processing. Moreover, images can be so large that they do not fit the main memory of a single computer. We address both issues by developing a distributed parallel algorithm for segmentation of large fluorescence microscopy images. The method is based on the versatile Discrete Region Competition algorithm, which has previously proven useful in microscopy image segmentation. The present distributed implementation decomposes the input image into smaller sub-images that are distributed across multiple computers. Using network communication, the computers orchestrate the collectively solving of the global segmentation problem. This not only enables segmentation of large images (we test images of up to 10¹⁰ pixels), but also accelerates segmentation to match the time scale of image acquisition. Such acquisition-rate image segmentation is a prerequisite for the smart microscopes of the future and enables online data compression and interactive experiments.     

Automatic detection of single fluorophores in live cells

Recent developments in light microscopy enable individual fluorophores to be observed in aqueous conditions. Biological molecules, labeled with a single fluorophore, can be localized as isolated spots of light when viewed by optical microscopy. Total internal reflection fluorescence microscopy greatly reduces background fluorescence and allows single fluorophores to be observed inside living cells. This advance in live-cell imaging means that the spatial and temporal dynamics of individual molecules can be measured directly. Because of the stochastic nature of single molecule behavior a statistically meaningful number of individual molecules must be detected and their separate trajectories in space and time stored and analyzed. Here, we describe digital image processing methods that we have devised for automatic detection and tracking of hundreds of molecules, observed simultaneously, in vitro and within living cells. Using this technique we have measured the diffusive behavior of pleckstrin homology domains bound to phosphoinositide phospholipids at the plasma membrane of live cultured mammalian cells. We found that mobility of these membrane-bound protein domains is dominated by mobility of the lipid molecule to which they are attached and is highly temperature dependent. Movement of PH domains isolated from the tail region of myosin-10 is consistent with a simple random walk, whereas, diffusion of intact PLC-delta1 shows behavior inconsistent with a simple random walk. Movement is rapid over short timescales but much slower at longer timescales. This anomalous behavior can be explained by movement being restricted to membrane regions of 0.7 microm diameter.     

Store-operated calcium entry inactivates at the germinal vesicle breakdown stage of Xenopus meiosis

Store-operated calcium entry (SOCE) is the predominant Ca(2+) influx pathway in non-excitable cells and is activated in response to depletion of intracellular Ca(2+) stores. We have studied SOCE regulation during Xenopus oocyte meiosis. SOCE can be measured readily in stage VI Xenopus oocytes arrested at the G(2)-M transition of the cell cycle, either by Ca(2+) imaging or by recording the SOCE current. However, following meiotic maturation, SOCE can no longer be activated by store depletion. We have characterized the time course of SOCE inactivation during oocyte maturation, and show that SOCE inactivates almost completely, in a very short time period, at the germinal vesicle breakdown stage of meiosis. This acute inactivation offers an opportunity to better understand SOCE regulation.     

Analysis of gene expression levels in individual bacterial cells without image segmentation

Studies of stochasticity in gene expression typically make use of fluorescent protein reporters, which permit the measurement of expression levels within individual cells by fluorescence microscopy. Analysis of such microscopy images is almost invariably based on a segmentation algorithm, where the image of a cell or cluster is analyzed mathematically to delineate individual cell boundaries. However segmentation can be ineffective for studying bacterial cells or clusters, especially at lower magnification, where outlines of individual cells are poorly resolved. Here we demonstrate an alternative method for analyzing such images without segmentation. The method employs a comparison between the pixel brightness in phase contrast vs fluorescence microscopy images. By fitting the correlation between phase contrast and fluorescence intensity to a physical model, we obtain well-defined estimates for the different levels of gene expression that are present in the cell or cluster. The method reveals the boundaries of the individual cells, even if the source images lack the resolution to show these boundaries clearly.     

A statistical framework for multiparameter analysis at the single-cell level

Phenotypic characterization of individual cells provides crucial insights into intercellular heterogeneity and enables access to information that is unavailable from ensemble averaged, bulk cell analyses. Single-cell studies have attracted significant interest in recent years and spurred the development of a variety of commercially available and research-grade technologies. To quantify cell-to-cell variability of cell populations, we have developed an experimental platform for real-time measurements of oxygen consumption (OC) kinetics at the single-cell level. Unique challenges inherent to these single-cell measurements arise, and no existing data analysis methodology is available to address them. Here we present a data processing and analysis method that addresses challenges encountered with this unique type of data in order to extract biologically relevant information. We applied the method to analyze OC profiles obtained with single cells of two different cell lines derived from metaplastic and dysplastic human Barrett's esophageal epithelium. In terms of method development, three main challenges were considered for this heterogeneous dynamic system: (i) high levels of noise, (ii) the lack of a priori knowledge of single-cell dynamics, and (iii) the role of intercellular variability within and across cell types. Several strategies and solutions to address each of these three challenges are presented. The features such as slopes, intercepts, breakpoint or change-point were extracted for every OC profile and compared across individual cells and cell types. The results demonstrated that the extracted features facilitated exposition of subtle differences between individual cells and their responses to cell-cell interactions. With minor modifications, this method can be used to process and analyze data from other acquisition and experimental modalities at the single-cell level, providing a valuable statistical framework for single-cell analysis.     

Muscarinic receptor activation determines the effects of store-operated Ca(2+)-entry on excitability and energy metabolism in pyramidal neurons

In various cell types, depletion of intracellular Ca(2+)-stores results in store-operated Ca(2+)-entry (SOCE) across the cellular membrane. However, the effects of SOCE on neuronal membrane excitability and mitochondrial functions in central neurons are not well defined. We investigated such cellular downstream effects in pyramidal neurons of rat organotypic hippocampal slice cultures by applying electrophysiological and fluorescence imaging techniques. We report that SOCE is associated with (i) elevations of Ca(2+)-concentration in individual neuronal mitochondria ([Ca(2+)](m)). In addition, SOCE can result in (ii) hyperpolarizing neuronal membrane currents, (iii) increase in extracellular K(+)-concentration ([K(+)](o)), (iv) mitochondrial membrane depolarization, and (v) changes in intracellular redox state (NAD(P)H and FAD fluorescence), the latter reflecting responses of energy metabolism. These additional downstream effects of SOCE required concomitant muscarinic receptor activation by carbachol or acetylcholine, and were suppressed by agonist washout or application of antagonist, atropine. We conclude that muscarinic receptor activation determines the downstream effects of SOCE on neuronal membrane excitability and energy metabolism. This mechanism might have significant impact on information processing and neurometabolic coupling in central neurons.     

A fast global fitting algorithm for fluorescence lifetime imaging microscopy based on image segmentation

Global fitting algorithms have been shown to improve effectively the accuracy and precision of the analysis of fluorescence lifetime imaging microscopy data. Global analysis performs better than unconstrained data fitting when prior information exists, such as the spatial invariance of the lifetimes of individual fluorescent species. The highly coupled nature of global analysis often results in a significantly slower convergence of the data fitting algorithm as compared with unconstrained analysis. Convergence speed can be greatly accelerated by providing appropriate initial guesses. Realizing that the image morphology often correlates with fluorophore distribution, a global fitting algorithm has been developed to assign initial guesses throughout an image based on a segmentation analysis. This algorithm was tested on both simulated data sets and time-domain lifetime measurements. We have successfully measured fluorophore distribution in fibroblasts stained with Hoechst and calcein. This method further allows second harmonic generation from collagen and elastin autofluorescence to be differentiated in fluorescence lifetime imaging microscopy images of ex vivo human skin. On our experimental measurement, this algorithm increased convergence speed by over two orders of magnitude and achieved significantly better fits.     

An Algorithm to Automate Yeast Segmentation and Tracking

Our understanding of dynamic cellular processes has been greatly enhanced by rapid advances in quantitative fluorescence microscopy. Imaging single cells has emphasized the prevalence of phenomena that can be difficult to infer from population measurements, such as all-or-none cellular decisions, cell-to-cell variability, and oscillations. Examination of these phenomena requires segmenting and tracking individual cells over long periods of time. However, accurate segmentation and tracking of cells is difficult and is often the rate-limiting step in an experimental pipeline. Here, we present an algorithm that accomplishes fully automated segmentation and tracking of budding yeast cells within growing colonies. The algorithm incorporates prior information of yeast-specific traits, such as immobility and growth rate, to segment an image using a set of threshold values rather than one specific optimized threshold. Results from the entire set of thresholds are then used to perform a robust final segmentation.     

Imaging of chlorophyll a fluorescence: theoretical and practical aspects of an emerging technique for the monitoring of photosynthetic performance

The development of chlorophyll (Chl) a fluorescence imaging systems has greatly increased the versatility of Chl a fluorometry as a non-invasive technique for the investigation of photosynthesis in plants and algae. For example, systems that image at the microscopic level have made it possible to measure PSII photochemical efficiencies from chloroplasts within intact leaves and from individual algal cells within mixed populations, while systems that image over much larger areas have been used to investigate heterogeneous patterns of photosynthetic performance across leaves and in screening programmes that image tens or even hundreds of plants simultaneously. In addition, it is now practical to use fluorescence imaging systems as real-time, multi-channel fluorometers, which can be used to record continuous fluorescence traces from multiple leaves, plants, or algal cells. This paper discusses some of the theoretical and practical issues associated with the imaging of Chl a fluorescence and with Chl a fluorometry in general. This discussion includes a review of the most commonly used Chl a fluorescence parameters.     

Differential RhoA Dynamics in Migratory and Stationary Cells Measured by FRET and Automated Image Analysis

Genetically-encoded biosensors based on fluorescence resonance energy transfer (FRET) have been widely applied to study the spatiotemporal regulation of molecular activity in live cells with high resolution. The efficient and accurate quantification of the large amount of imaging data from these single-cell FRET measurements demands robust and automated data analysis. However, the nonlinear movement of live cells presents tremendous challenge for this task. Based on image registration of the single-cell movement, we have developed automated image analysis methods to track and quantify the FRET signals within user-defined subcellular regions. In addition, the subcellular pixels were classified according to their associated FRET signals and the dynamics of the clusters analyzed. The results revealed that the EGF-induced reduction of RhoA activity in migratory HeLa cells is significantly less than that in stationary cells. Furthermore, the RhoA activity is polarized in the migratory cells, with the gradient of polarity oriented toward the opposite direction of cell migration. In contrast, there is a lack of consistent preference in RhoA polarity among stationary cells. Therefore, our image analysis methods can provide powerful tools for high-throughput and systematic investigation of the spatiotemporal molecular activities in regulating functions of live cells with their shapes and positions continuously changing in time.     

Controlled light-exposure microscopy reduces photobleaching and phototoxicity in fluorescence live-cell imaging

Fluorescence microscopy of living cells enables visualization of the dynamics and interactions of intracellular molecules. However, fluorescence live-cell imaging is limited by photobleaching and phototoxicity induced by the excitation light. Here we describe controlled light-exposure microscopy (CLEM), a simple imaging approach that reduces photobleaching and phototoxicity two- to tenfold, depending on the fluorophore distribution in the object. By spatially controlling the light-exposure time, CLEM reduces the excitation-light dose without compromising image quality. We show that CLEM reduces photobleaching sevenfold in tobacco plant cells expressing microtubule-associated GFP-MAP4 and reduces production of reactive oxygen species eightfold and prolongs cell survival sixfold in HeLa cells expressing chromatin-associated H2B-GFP. In addition, CLEM increases the dynamic range of the fluorescence intensity at least twofold.     

Store-operated calcium entry in physiology and pathology of mammalian cells

One of the numerous calcium-involving processes in mammalian cells is store-operated calcium entry (SOCE) -- the process in which depletion of calcium stores in the endoplasmic reticulum (ER) induces calcium influx from the extracellular space. Previously supposed to function only in non-excitable cells, SOCE is now known to play a role also in such excitable cells as neurons, muscles and neuroendocrine cells and is found in many different cell types. SOCE participates not only in processes dependent on ER calcium level but also specifically regulates some important processes such as cAMP production, T lymphocyte activation or induction of long-term potentiation. Impairment of SOCE can be an element of numerous disorders such as acute pancreatitis, primary immunodeficiency and, since it can take part in apoptosis or cell cycle regulation, SOCE may also be partially responsible for such serious disorders as Alzheimer disease and many types of cancer. Even disturbances in the 'servant' role of maintaining ER calcium level may cause serious effects because they can lead to ER homeostasis disturbance, influencing gene expression, protein synthesis and processing, and the cell cycle.     

Cell-to-cell variation in store-operated calcium entry in HEK-293 cells and its impact on the interpretation of data from stable clones expressing exogenous calcium channels

To investigate the effect of cell-to-cell variation in store-operated calcium entry (SOCE) on the evaluation of data from stable cell clones selected following gene transfection, we measured SOCE in 2700 individual HEK-293 cells from the parent population and in 1900 individual cells from a clonal subpopulation of HEK-293 cells. We applied statistical resampling techniques to model conditions where one would compare the average SOCE in n control clones to the average SOCE in n experimental clones (n = 1-200). For an overexpression experiment with n = 1, there is a 27% chance of observing a 100% or higher difference in SOCE between clones, with n = 10 there is a 34% probability of observing a 20% or greater difference in SOCE, and with n = 100, there is less than a 10% chance of seeing a 10% or greater difference in SOCE, based solely on random selection of clones from the parent HEK-293 cell population. To assure that the degree of cell-to-cell variation was predictive of the degree of clone-to-clone variation, we measured SOCE in 270 clones, each arising from a single cell, and found the variation to be very similar to that observed for individual cells.     

Automated method for the rapid and precise estimation of adherent cell culture characteristics from phase contrast microscopy images

The quantitative determination of key adherent cell culture characteristics such as confluency, morphology, and cell density is necessary for the evaluation of experimental outcomes and to provide a suitable basis for the establishment of robust cell culture protocols. Automated processing of images acquired using phase contrast microscopy (PCM), an imaging modality widely used for the visual inspection of adherent cell cultures, could enable the non‐invasive determination of these characteristics. We present an image‐processing approach that accurately detects cellular objects in PCM images through a combination of local contrast thresholding and post hoc correction of halo artifacts. The method was thoroughly validated using a variety of cell lines, microscope models and imaging conditions, demonstrating consistently high segmentation performance in all cases and very short processing times (<1 s per 1,208 × 960 pixels image). Based on the high segmentation performance, it was possible to precisely determine culture confluency, cell density, and the morphology of cellular objects, demonstrating the wide applicability of our algorithm for typical microscopy image processing pipelines. Furthermore, PCM image segmentation was used to facilitate the interpretation and analysis of fluorescence microscopy data, enabling the determination of temporal and spatial expression patterns of a fluorescent reporter. We created a software toolbox (PHANTAST) that bundles all the algorithms and provides an easy to use graphical user interface. Source‐code for MATLAB and ImageJ is freely available under a permissive open‐source license. Biotechnol. Bioeng. 2014;111: 504–517. © 2013 Wiley Periodicals, Inc.