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.     

Quantification of Local Morphodynamics and Local GTPase Activity by Edge Evolution Tracking

Advances in time-lapse fluorescence microscopy have enabled us to directly observe dynamic cellular phenomena. Although the techniques themselves have promoted the understanding of dynamic cellular functions, the vast number of images acquired has generated a need for automated processing tools to extract statistical information. A problem underlying the analysis of time-lapse cell images is the lack of rigorous methods to extract morphodynamic properties. Here, we propose an algorithm called edge evolution tracking (EET) to quantify the relationship between local morphological changes and local fluorescence intensities around a cell edge using time-lapse microscopy images. This algorithm enables us to trace the local edge extension and contraction by defining subdivided edges and their corresponding positions in successive frames. Thus, this algorithm enables the investigation of cross-correlations between local morphological changes and local intensity of fluorescent signals by considering the time shifts. By applying EET to fluorescence resonance energy transfer images of the Rho-family GTPases Rac1, Cdc42, and RhoA, we examined the cross-correlation between the local area difference and GTPase activity. The calculated correlations changed with time-shifts as expected, but surprisingly, the peak of the correlation coefficients appeared with a 6–8 min time shift of morphological changes and preceded the Rac1 or Cdc42 activities. Our method enables the quantification of the dynamics of local morphological change and local protein activity and statistical investigation of the relationship between them by considering time shifts in the relationship. Thus, this algorithm extends the value of time-lapse imaging data to better understand dynamics of cellular function.     

Oufti: an integrated software package for high‐accuracy,high‐throughput quantitative microscopy analysis

With the realization that bacteria display phenotypic variability among cells and exhibit complex subcellular organization critical for cellular function and behavior, microscopy has re‐emerged as a primary tool in bacterial research during the last decade. However, the bottleneck in today's single‐cell studies is quantitative image analysis of cells and fluorescent signals. Here, we address current limitations through the development of Oufti, a stand‐alone, open‐source software package for automated measurements of microbial cells and fluorescence signals from microscopy images. Oufti provides computational solutions for tracking touching cells in confluent samples, handles various cell morphologies, offers algorithms for quantitative analysis of both diffraction and non‐diffraction‐limited fluorescence signals and is scalable for high‐throughput analysis of massive datasets, all with subpixel precision. All functionalities are integrated in a single package. The graphical user interface, which includes interactive modules for segmentation, image analysis and post‐processing analysis, makes the software broadly accessible to users irrespective of their computational skills.     

Automated cell identification and tracking using nanoparticle moving-light-displays

An automated technique for the identification, tracking and analysis of biological cells is presented. It is based on the use of nanoparticles, enclosed within intra-cellular vesicles, to produce clusters of discrete, point-like fluorescent, light sources within the cells. Computational analysis of these light ensembles in successive time frames of a movie sequence, using k-means clustering and particle tracking algorithms, provides robust and automated discrimination of live cells and their motion and a quantitative measure of their proliferation. This approach is a cytometric version of the moving light display technique which is widely used for analyzing the biological motion of humans and animals. We use the endocytosis of CdTe/ZnS, core-shell quantum dots to produce the light displays within an A549, epithelial, lung cancer cell line, using time-lapse imaging with frame acquisition every 5 minutes over a 40 hour time period. The nanoparticle moving light displays provide simultaneous collection of cell motility data, resolution of mitotic traversal dynamics and identification of familial relationships allowing construction of multi-parameter lineage trees.     

Precise nanometer localization analysis for individual fluorescent probes

Calculation of the centroid of the images of individual fluorescent particles and molecules allows localization and tracking in light microscopes to a precision about an order of magnitude greater than the microscope resolution. The factors that limit the precision of these techniques are examined and a simple equation derived that describes the precision of localization over a wide range of conditions. In addition, a localization algorithm motivated from least-squares fitting theory is constructed and tested both on image stacks of 30-nm fluorescent beads and on computer-generated images (Monte Carlo simulations). Results from the algorithm show good agreement with the derived precision equation for both the simulations and actual images. The availability of a simple equation to describe localization precision helps investigators both in assessing the quality of an experimental apparatus and in directing attention to the factors that limit further improvement. The precision of localization scales as the inverse square root of the number of photons in the spot for the shot noise limited case and as the inverse of the number of photons for the background noise limited case. The optimal image magnification depends on the expected number of photons and background noise, but, for most cases of interest, the pixel size should be about equal to the standard deviation of the point spread function.     

Precise particle tracking against a complicated background: polynomial fitting with Gaussian weight

We present a new particle tracking software algorithm designed to accurately track the motion of low-contrast particles against a background with large variations in light levels. The method is based on a polynomial fit of the intensity around each feature point, weighted by a Gaussian function of the distance from the centre, and is especially suitable for tracking endogeneous particles in the cell, imaged with bright field, phase contrast or fluorescence optical microscopy. Furthermore, the method can simultaneously track particles of all different sizes, and allows significant freedom in their shape. The algorithm is evaluated using the quantitative measures of accuracy and precision of previous authors, using simulated images at variable signal-to-noise ratios. To these we add new tests: the error due to a non-uniform background, and the error due to two particles approaching each other. Finally the tracking of particles in real cell images is demonstrated. The method is made freely available for non-commercial use as a software package with a graphical user-interface, which can be run within the Matlab programming environment.     

Tracking of single fluorescent particles in three dimensions: use of cylindrical optics to encode particle position.

We present a novel optical technique for three-dimensional tracking of single fluorescent particles using a modified epifluorescence microscope containing a weak cylindrical lens in the detection optics and a microstepper-controlled fine focus. Images of small, fluorescent particles were circular in focus but ellipsoidal above and below focus; the major axis of the ellipsoid shifted by 90 degrees in going through focus. Particle z position was determined from the image shape and orientation by applying a peak detection algorithm to image projections along the x and y axes; x, y position was determined from the centroid of the particle image. Typical spatial resolution was 12 nm along the optical axis and 5 nm in the image plane with a maximum sampling rate of 3-4 Hz. The method was applied to track fluorescent particles in artificial solutions and living cells. In a solution of viscosity 30 cP, the mean squared distance (MSD) traveled by a 264 nm diameter rhodamine-labeled bead was linear with time to 20 s. The measured diffusion coefficient, 0.0558 +/- 0.001 micron2/s (SE, n = 4), agreed with the theoretical value of 0.0556 micron2/s. Statistical variability of MSD curves for a freely diffusing bead was in quantitative agreement with Monte Carlo simulations of three-dimensional random walks. In a porous glass matrix, the MSD data was curvilinear and showed reduced bead diffusion. In cytoplasm of Swiss 3T3 fibroblasts, bead diffusion was restricted. The water permeability in individual Chinese Hamster Ovary cells was measured from the z movement of a fluorescent bead fixed at the cell surface in response osmotic gradients; water permeability was increased by > threefold in cells expressing CHIP28 water channels. The simplicity and precision of this tracking method may be useful to quantify the complex trajectories of fluorescent particles in living cells.     

A Highlights from MBoC Selection: Measuring fast gene dynamics in single cells with time-lapse luminescence microscopy

Time-lapse fluorescence microscopy is an important tool for measuring in vivo gene dynamics in single cells. However, fluorescent proteins are limited by slow chromophore maturation times and the cellular autofluorescence or phototoxicity that arises from light excitation. An alternative is luciferase, an enzyme that emits photons and is active upon folding. The photon flux per luciferase is significantly lower than that for fluorescent proteins. Thus time-lapse luminescence microscopy has been successfully used to track gene dynamics only in larger organisms and for slower processes, for which more total photons can be collected in one exposure. Here we tested green, yellow, and red beetle luciferases and optimized substrate conditions for in vivo luminescence. By combining time-lapse luminescence microscopy with a microfluidic device, we tracked the dynamics of cell cycle genes in single yeast with subminute exposure times over many generations. Our method was faster and in cells with much smaller volumes than previous work. Fluorescence of an optimized reporter (Venus) lagged luminescence by 15–20 min, which is consistent with its known rate of chromophore maturation in yeast. Our work demonstrates that luciferases are better than fluorescent proteins at faithfully tracking the underlying gene expression.     

Characterization and efficacy of PKH26 as a probe to study the replication history of the human hematopoietic KG1a progenitor cell line

The PKH26 dye can, in principle, be used for the study of asymmetric cell divisions (ASDs). A requirement for the identification of ASDs based on fluorescence intensity is that the PKH26 dye is distributed equally between daughter cells at each division, but this has not been demonstrated at a single-cell level. The efficacy of PKH26 as a probe for the study of ASDs was examined using the human hematopoietic KG1a cell. An automated time-lapse fluorescent microscope system was used to determine changes in cell size and fluorescence intensity during culture, and track cell divisions. The images of daughter cells were analyzed using the Isee software to determine the distribution of PKH26 dye between daughter cells. Ratios of cell size, mean fluorescence intensity, and total fluorescence intensity were calculated by dividing the values for one daughter cell by the value of the other daughter cell. The ratios for cell size, mean intensity, and total intensity were 1.13 +/- 0.12, 1.08 +/- 0.07, and 1.15 +/- 0.14 (mean +/- SD), respectively. Thus, PKH26 is not distributed equally to both daughter cells upon cell division. However, the replication history of individual KG1a cells can be reliably deduced for up to three divisions based solely on the mean and total fluorescence intensity of the PKH26 dye, using PKH26 concentrations below the chemical and phototoxic limits (2 microM).     

Following cell-fate in E. coli after infection by phage lambda

The system comprising bacteriophage (phage) lambda and the bacterium E. coli has long served as a paradigm for cell-fate determination. Following the simultaneous infection of the cell by a number of phages, one of two pathways is chosen: lytic (virulent) or lysogenic (dormant). We recently developed a method for fluorescently labeling individual phages, and were able to examine the post-infection decision in real-time under the microscope, at the level of individual phages and cells. Here, we describe the full procedure for performing the infection experiments described in our earlier work. This includes the creation of fluorescent phages, infection of the cells, imaging under the microscope and data analysis. The fluorescent phage is a "hybrid", co-expressing wild- type and YFP-fusion versions of the capsid gpD protein. A crude phage lysate is first obtained by inducing a lysogen of the gpD-EYFP (Enhanced Yellow Fluorescent Protein) phage, harboring a plasmid expressing wild type gpD. A series of purification steps are then performed, followed by DAPI-labeling and imaging under the microscope. This is done in order to verify the uniformity, DNA packaging efficiency, fluorescence signal and structural stability of the phage stock. The initial adsorption of phages to bacteria is performed on ice, then followed by a short incubation at 35°C to trigger viral DNA injection. The phage/bacteria mixture is then moved to the surface of a thin nutrient agar slab, covered with a coverslip and imaged under an epifluorescence microscope. The post-infection process is followed for 4 hr, at 10 min interval. Multiple stage positions are tracked such that ~100 cell infections can be traced in a single experiment. At each position and time point, images are acquired in the phase-contrast and red and green fluorescent channels. The phase-contrast image is used later for automated cell recognition while the fluorescent channels are used to characterize the infection outcome: production of new fluorescent phages (green) followed by cell lysis, or expression of lysogeny factors (red) followed by resumed cell growth and division. The acquired time-lapse movies are processed using a combination of manual and automated methods. Data analysis results in the identification of infection parameters for each infection event (e.g. number and positions of infecting phages) as well as infection outcome (lysis/lysogeny). Additional parameters can be extracted if desired.     

Tracking single Kinesin molecules in the cytoplasm of mammalian cells

Understanding dynamic cellular processes requires precise knowledge of the distribution, transport, and interactions of individual molecules in living cells. Despite recent progress in in vivo imaging, it has not been possible to express and directly track single molecules in the cytoplasm of live cells. Here, we overcome these limitations by combining fluorescent protein-labeling with high resolution total internal reflection fluorescence microcopy, using the molecular motor Kinesin-1 as model system. First, we engineered a three-tandem monomeric Citrine tag for genetic labeling of individual molecules and expressed this motor in COS cells. Detailed analysis of the quantized photobleaching behavior of individual fluorescent spots demonstrates that we are indeed detecting single proteins in the cytoplasm of live cells. Tracking the movement of individual cytoplasmic molecules reveals that individual Kinesin-1 motors in vivo move with an average speed of 0.78 +/- 0.11 microm/s and display an average run length of 1.17 +/- 0.38 microm, which agrees well with in vitro measurements. Thus, Kinesin-1's speed and processivity are not upregulated or hindered by macromolecular crowding. Second, we demonstrate that standard deviation maps of the fluorescence intensity computed from single molecule image sequences can be used to reveal important physiological information about infrequent cellular events in the noisy fluorescence background of live cells. Finally, we show that tandem fluorescent protein tags enable single-molecule, in vitro analyses of extracted, mammalian-expressed proteins. Thus, by combining direct genetic labeling and single molecule imaging in vivo, our work establishes an important new biophysical method for observing single molecules expressed and localized in the mammalian cytoplasm.     

High-throughput RNAi screening by time-lapse imaging of live human cells

RNA interference (RNAi) is a powerful tool to study gene function in cultured cells. Transfected cell microarrays in principle allow high-throughput phenotypic analysis after gene knockdown by microscopy. But bottlenecks in imaging and data analysis have limited such high-content screens to endpoint assays in fixed cells and determination of global parameters such as viability. Here we have overcome these limitations and developed an automated platform for high-content RNAi screening by time-lapse fluorescence microscopy of live HeLa cells expressing histone-GFP to report on chromosome segregation and structure. We automated all steps, including printing transfection-ready small interfering RNA (siRNA) microarrays, fluorescence imaging and computational phenotyping of digital images, in a high-throughput workflow. We validated this method in a pilot screen assaying cell division and delivered a sensitive, time-resolved phenoprint for each of the 49 endogenous genes we suppressed. This modular platform is scalable and makes the power of time-lapse microscopy available for genome-wide RNAi screens.     

Electronic light microscopy: present capabilities and future prospects

Electronic light microscopy involves the combination of microscopic techniques with electronic imaging and digital image processing, resulting in dramatic improvements in image quality and ease of quantitative analysis. In this review, after a brief definition of digital images and a discussion of the sampling requirements for the accurate digital recording of optical images, I discuss the three most important imaging modalities in electronic light microscopy-video-enhanced contrast microscopy, digital fluorescence microscopy and confocal scanning microscopy-considering their capabilities, their applications, and recent developments that will increase their potential. Video-enhanced contrast microscopy permits the clear visualisation and real-time dynamic recording of minute objects such as microtubules, vesicles and colloidal gold particles, an order of magnitude smaller than the resolution limit of the light microscope. It has revolutionised the study of cellular motility, and permits the quantitative tracking of organelles and gold-labelled membrane bound proteins. In combination with the technique of optical trapping (optical tweezers), it permits exquisitely sensitive force and distance measurements to be made on motor proteins. Digital fluorescence microscopy enables low-light-level imaging of fluorescently labelled specimens. Recent progress has involved improvements in cameras, fluorescent probes and fluorescent filter sets, particularly multiple bandpass dichroic mirrors, and developments in multiparameter imaging, which is becoming particularly important for in situ hybridisation studies and automated image cytometry, fluorescence ratio imaging, and time-resolved fluorescence. As software improves and small computers become more powerful, computational techniques for out-of-focus blur deconvolution and image restoration are becoming increasingly important. Confocal microscopy permits convenient, high-resolution, non-invasive, blur-free optical sectioning and 3D image acquisition, but suffers from a number of limitations. I discuss advances in confocal techniques that address the problems of temporal resolution, spherical and chromatic aberration, wavelength flexibility and cross-talk between fluorescent channels, and describe new optics to enhance axial resolution and the use of two-photon excitation to reduce photobleaching. Finally, I consider the desirability of establishing a digital image database, the BioImage database, which would permit the archival storage of, and public Internet access to, multidimensional image data from all forms of biological microscopy. Submission of images to the BioImage database would be made in coordination with the scientific publication of research results based upon these data. In the context of electronic light microscopy, this would be particularly useful for three-dimensional images of cellular structure and video sequences of dynamic cellular processes, which are otherwise hard to communicate. However, it has the wider significance of allowing correlative studies on data obtained from many different microscopies and from sequence and crystallographic investigations. It also opens the door to interactive hypermedia access to the multidimensional image data, and multimedia publishing ventures based upon this.Presented at the XXXVII Symposium of the Society for Histochemistry, 23 September 1995, Rigi Kaltbad, Switzerland     

Vertebrate neural stem cell segmentation, tracking and lineaging with validation and editing

This protocol and the accompanying software program called LEVER (lineage editing and validation) enable quantitative automated analysis of phase-contrast time-lapse images of cultured neural stem cells. Images are captured at 5-min intervals over a period of 5-15 d as the cells proliferate and differentiate. LEVER automatically segments, tracks and generates lineage trees of the stem cells from the image sequence. In addition to generating lineage trees capturing the population dynamics of clonal development, LEVER extracts quantitative phenotypic measurements of cell location, shape, movement and size. When available, the system can include biomolecular markers imaged using fluorescence. It then displays the results to the user for highly efficient inspection and editing to correct any errors in the segmentation, tracking or lineaging. To enable high-throughput inspection, LEVER incorporates features for rapid identification of errors and for learning from user-supplied corrections to automatically identify and correct related errors.     

Mapping Diffusion in a Living Cell via the Phasor Approach

Diffusion of a fluorescent protein within a cell has been measured using either fluctuation-based techniques (fluorescence correlation spectroscopy (FCS) or raster-scan image correlation spectroscopy) or particle tracking. However, none of these methods enables us to measure the diffusion of the fluorescent particle at each pixel of the image. Measurement using conventional single-point FCS at every individual pixel results in continuous long exposure of the cell to the laser and eventual bleaching of the sample. To overcome this limitation, we have developed what we believe to be a new method of scanning with simultaneous construction of a fluorescent image of the cell. In this believed new method of modified raster scanning, as it acquires the image, the laser scans each individual line multiple times before moving to the next line. This continues until the entire area is scanned. This is different from the original raster-scan image correlation spectroscopy approach, where data are acquired by scanning each frame once and then scanning the image multiple times. The total time of data acquisition needed for this method is much shorter than the time required for traditional FCS analysis at each pixel. However, at a single pixel, the acquired intensity time sequence is short; requiring nonconventional analysis of the correlation function to extract information about the diffusion. These correlation data have been analyzed using the phasor approach, a fit-free method that was originally developed for analysis of FLIM images. Analysis using this method results in an estimation of the average diffusion coefficient of the fluorescent species at each pixel of an image, and thus, a detailed diffusion map of the cell can be created.     

Real-time cross-correlation image analysis of early events in IgE receptor signaling

Signaling in mast cells and basophils is mediated through IgE and its high affinity cell surface receptor, FcepsilonRI. Crosslinking of the receptors by a cognate multivalent antigen leads to degranulation and release of mediators of the allergic immune response. Using multicolor fluorescence confocal microscopy, we probed the spatio-temporal dynamics of early events in the IgE receptor signal cascade. We monitored the recruitment of GFP-/CFP-labeled signaling proteins by acquiring sequential images with time resolution of 3 s during stimulation of RBL-2H3 mast cells with multivalent antigen. A fluorescent tag on the antigen allowed us to visualize the plasma membrane localization of crosslinked receptors, and fluorescent cholera toxin B served as a plasma membrane marker. We developed an automated image analysis scheme to quantify the recruitment of fluorescent intracellular proteins to the plasma membrane and to assess the time-dependent colocalization of these and other membrane-associated proteins with crosslinked receptors as measured by cross-correlation between the plasma membrane distributions of the two fluorophores. This automated method permits analysis of thousands of individual images from multiple experiments for each cross-correlation pair. We systematically applied this analysis to characterize stimulated interactions of IgE receptors with several signaling proteins, including the tyrosine kinases Lyn and Syk, and the adaptor protein LAT. Notably, for Syk-CFP we observed a rapid stimulated translocation to the plasma membrane but very little colocalization with aggregated receptors. Our results demonstrate the utility of this simple, automated method to monitor protein interactions quantitatively during cell signaling.     

Feature point tracking and trajectory analysis for video imaging in cell biology

This paper presents a computationally efficient, two-dimensional, feature point tracking algorithm for the automated detection and quantitative analysis of particle trajectories as recorded by video imaging in cell biology. The tracking process requires no a priori mathematical modeling of the motion, it is self-initializing, it discriminates spurious detections, and it can handle temporary occlusion as well as particle appearance and disappearance from the image region. The efficiency of the algorithm is validated on synthetic video data where it is compared to existing methods and its accuracy and precision are assessed for a wide range of signal-to-noise ratios. The algorithm is well suited for video imaging in cell biology relying on low-intensity fluorescence microscopy. Its applicability is demonstrated in three case studies involving transport of low-density lipoproteins in endosomes, motion of fluorescently labeled Adenovirus-2 particles along microtubules, and tracking of quantum dots on the plasma membrane of live cells. The present automated tracking process enables the quantification of dispersive processes in cell biology using techniques such as moment scaling spectra.     

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.     

Joint tagging assisted fluctuation nanoscopy enables fast high‐density super‐resolution imaging

In fluctuation‐based optical nanoscopy, investigating high‐density labeled subcellular structures with high fidelity has been a significant challenge. In this study, based on super‐resolution radial fluctuation (SRRF) microscopy, the joint tagging (JT) strategy is employed to enable fast high‐density nanoscopic imaging and tracking. In fixed cell experiment, multiple types of quantum dots with distinguishable fluorescence spectra are jointly tagged to subcellular microtubules. In each spectral channel, the decrease in labeling density guarantees the high‐fidelity super‐resolution reconstruction using SRRF microscopy. Subsequently, the combination of all spectral channels achieves high‐density super‐resolution imaging of subcellular microtubules with a resolution of ~62 nm using JT assisted SRRF technique. In the live‐cell experiment, 3‐channel JT is utilized to track the dynamic motions of high‐density toxin‐induced lipid clusters for 1 minute, achieving the simultaneous tracking of many individual toxin‐induced lipid clusters spatially distributed significantly below the optical diffraction limit in living cells.