SuperSegger: robust image segmentation,analysis and lineage tracking of bacterial cells

Many quantitative cell biology questions require fast yet reliable automated image segmentation to identify and link cells from frame‐to‐frame, and characterize the cell morphology and fluorescence. We present SuperSegger, an automated MATLAB‐based image processing package well‐suited to quantitative analysis of high‐throughput live‐cell fluorescence microscopy of bacterial cells. SuperSegger incorporates machine‐learning algorithms to optimize cellular boundaries and automated error resolution to reliably link cells from frame‐to‐frame. Unlike existing packages, it can reliably segment microcolonies with many cells, facilitating the analysis of cell‐cycle dynamics in bacteria as well as cell‐contact mediated phenomena. This package has a range of built‐in capabilities for characterizing bacterial cells, including the identification of cell division events, mother, daughter and neighbouring cells, and computing statistics on cellular fluorescence, the location and intensity of fluorescent foci. SuperSegger provides a variety of postprocessing data visualization tools for single cell and population level analysis, such as histograms, kymographs, frame mosaics, movies and consensus images. Finally, we demonstrate the power of the package by analyzing lag phase growth with single cell resolution.     

Computer-based tracking of living cells

A computer-based tracing technique has been developed to follow the movement of living cells and keep them centered in the field of view of an optical microscope. With the use of an image-processing system, the video image of a cell can be sufficiently processed to allow computer-recognition of the cell boundaries. Determination of the location of the center of the cell enables comparison of successive cell positions and correction for any cell movement. In order to illustrate the versatility of this technique, patterns of movement were obtained of cancerous and non-cancerous cells in an effort to determine the difference in motility between the two cell types. After examination of the data gathered, it was found that there is no difference in the motility between the two cell types over 1-h periods.     

Probing and tracking organelles in living plant cells

Intracellular organelle movements and positioning play pivotal roles in enabling plants to proliferate life efficiently and to survive diverse environmental stresses. The elaborate dissection of organelle dynamics and their underlying mechanisms (e.g., the role of the cytoskeleton in organelle movements) largely depends on the advancement and efficiency of organelle tracking systems. Here, we provide an overview of some recently developed tools for labeling and tracking organelle dynamics in living plant cells.     

Probing and tracking organelles in living plant cells

Intracellular organelle movements and positioning play pivotal roles in enabling plants to proliferate life efficiently and to survive diverse environmental stresses. The elaborate dissection of organelle dynamics and their underlying mechanisms (e.g., the role of the cytoskeleton in organelle movements) largely depends on the advancement and efficiency of organelle tracking systems. Here, we provide an overview of some recently developed tools for labeling and tracking organelle dynamics in living plant cells.     

The disposal of dying cells in living tissues

Cells continuously die and disappear from the midst of living tissues. However, some of their constituents survive. DNA is horizontally transferred to phagocytic cells, and apoptotic cell antigens shape the immune repertoire. When massive apoptosis occurs, which overwhelms tissue scavenger cells, or when the function of phagocytes abates, dying cells escape clearance in vivo. Remnant dying cells come to phagocytes disguised: factors capable to envelop their membranes pervade the entire organism, or are generated in given tissues. Some are constitutively present, while other are generated during early or late phases of the inflammatory response, possibly to face the further burden of the dead inflammatory cells. This camouflage influences the disposal of the corpses: decoying molecules either bridge the corpse to the phagocyte or hide it. Furthermore, factors associated to the plasma membrane of the apoptotic cell shape the signals the phagocyte releases in situ. Finally, molecules contained or released by the dying cell alter the apprehension by the phagocyte of its prey, influencing its immunogenicity.     

Imaging calcium dynamics in living plant cells and tissues

The central role of Ca²⁺ signalling in plants is now well established. Much of our recent research has been based on the premise that the direct demonstration of signal-response coupling via Ca²⁺ requires the imaging or measurement of cytosolic free Ca²⁺ in living cells. Methods (confocal microscopy, fluorescence ratio imaging and photon counting imaging) which we use for imaging Ca²⁺ with fluorescent dyes or recombinant aequorin, are described. Approaches for using dyes are now routine for many plant cells. However, the imaging Ca²⁺ in whole tissues of plants genetically transformed with the aequorin gene is a very new development. We predict that this method, first employed in our laboratory, will bring about a revolution in our understanding of Ca²⁺ signalling at the multicellular level.     

Advances in fluorescent tracking of nucleic acids in living cells

Nucleic acids are typically detected in morphologically preserved fixed cells and tissues using in situ hybridization techniques. This review discusses a variety of established and more challenging fluorescence-based methods for the detection and tracking of DNA or RNA sequences in living cells. Over the past few years, various fluorescent in vivo labeling methods have been developed, and dedicated microscope and image analysis tools have been designed. These advances in technologies indicate that live-cell imaging of nucleic acids is likely to become a standard research tool for understanding genome organization and gene expression regulation in the near future. Recent live-cell imaging studies have already provided important insights into the dynamic behaviors of chromatin and RNAs in the cell.     

Visualizing loss of heterozygosity in living mouse cells and tissues

Chronic exposure to oxidative stress especially to highly reactive hydroxyl radicals (HO*) could damage biomolecules, particularly DNA, that in turn would accelerate onset of degenerative diseases. In the present study a few standard phytochemicals (vitamin C, gallic acid, catechin, apigenin, naringenin and naringin) and plant extracts (Hippophae rhamnoides kernel (HRK), Syzygium cumini kernel (SCK) and Punica granatum pericarp (PGP)) were evaluated for their potential to protect/damage DNA in Fenton's system using in vitro models. The results indicated a significant DNA protective effect for naringin and PGP whereas other phytochemicals/extracts showed DNA damaging effect similar to or more than that of control value. The phytochemicals/extracts were also evaluated for their antioxidant and iron chelation properties. In general, the phytochemicals/extracts with high antioxidant activity but without iron chelation capacity failed to protect DNA in Fenton's system, suggesting that iron chelation was an essential requirement for the phytochemicals studied here to retard HO* generation by Fenton's reaction. This was demonstrated by the high iron chelation capacity of naringin and PGP (83.67% and 68.67% respectively) and their DNA protective effect. Commonly consumed phytochemicals such as vitamin C and gallic acid with their high reducing power and at higher physiological concentration, could regenerate free iron for Fenton's reaction leading to DNA damage as shown here.     

Automated time-lapse microscopy and high-resolution tracking of cell migration

We describe a novel fully automated high-throughput time-lapse microscopy system and evaluate its performance for precisely tracking the motility of several glioma and osteoblastic cell lines. Use of this system revealed cell motility behavior not discernable with conventional techniques by collecting data (1) from closely spaced time points (minutes), (2) over long periods (hours to days), (3) from multiple areas of interest, (4) in parallel under several different experimental conditions. Quantitation of true individual and average cell velocity and path length was obtained with high spatial and temporal resolution in “scratch” or “wound healing” assays. This revealed unique motility dynamics of drug-treated and adhesion molecule-transfected cells and, thus, this is a considerable improvement over current methods of measurement and analysis. Several fluorescent vital labeling methods commonly used for end-point analyses (GFP expression, DiO lipophilic dye, and Qtracker nanocrystals) were found to be useful for time-lapse studies under specific conditions that are described. To illustrate one application, fluorescently labeled tumor cells were seeded onto cell monolayers expressing ectopic adhesion molecules, and this resulted in consistently reduced tumor cell migration velocities. These highly quantitative time-lapse analysis methods will promote the creation of new cell motility assays and increase the resolution and accuracy of existing assays.Joseph S. Fotos and Vivek P. Patel contributed equally to this work     

Exploring dynamics in living cells by tracking single particles

In the last years, significant advances in microscopy techniques and the introduction of a novel technology to label living cells with genetically encoded fluorescent proteins revolutionized the field of Cell Biology. Our understanding on cell dynamics built from snapshots on fixed specimens has evolved thanks to our actual capability to monitor in real time the evolution of processes in living cells. Among these new tools, single particle tracking techniques were developed to observe and follow individual particles. Hence, we are starting to unravel the mechanisms driving the motion of a wide variety of cellular components ranging from organelles to protein molecules by following their way through the cell. In this review, we introduce the single particle tracking technology to new users. We briefly describe the instrumentation and explain some of the algorithms commonly used to locate and track particles. Also, we present some common tools used to analyze trajectories and illustrate with some examples the applications of single particle tracking to study dynamics in living cells.     

Mechanics of living cells measured by laser tracking microrheology

To establish laser-tracking microrheology (LTM) as a new technique for quantifying cytoskeletal mechanics, we measure viscoelastic moduli with wide bandwidth (5 decades) within living cells. With the first subcellular measurements of viscoelastic phase angles, LTM provides estimates of solid versus liquid behavior at different frequencies. In LTM, the viscoelastic shear moduli are inferred from the Brownian motion of particles embedded in the cytoskeletal network. Custom laser optoelectronics provide sub-nanometer and near-microsecond resolution of particle trajectories. The kidney epithelial cell line, COS7, has numerous spherical lipid-storage granules that are ideal probes for noninvasive LTM. Although most granules are percolating through perinuclear spaces, a subset of perinuclear granules is embedded in dense viscoelastic cytoplasm. Over all time scales embedded particles exhibit subdiffusive behavior and are not merely tethered by molecular motors. At low frequencies, lamellar regions (820 +/- 520 dyne/cm(2)) are more rigid than viscoelastic perinuclear regions (330 +/- 250 dyne/cm(2), p < 0.0001), but spectra converge at high frequencies. Although the actin-disrupting agent, latrunculin A, softens and liquefies lamellae, physiological levels of F-actin, alone (11 +/- 1.2 dyne/cm(2)) are approximately 70-fold softer than lamellae. Therefore, F-actin is necessary for lamellae mechanics, but not sufficient. Furthermore, in time-lapse of apparently quiescent cells, individual lamellar granules can show approximately 4-fold changes in moduli that last >10 s. Over a broad range of frequencies (0.1-30, 000 rad/s), LTM provides a unique ability to noninvasively quantify dynamic, local changes in cell viscoelasticity.     

Protein localization in living cells and tissues using FRET and FLIM

Interacting proteins assemble into molecular machines that control cellular homeostasis in living cells. While the in vitro screening methods have the advantage of providing direct access to the genetic information encoding unknown protein partners, they do not allow direct access to interactions of these protein partners in their natural environment inside the living cell. Using wide-field, confocal, or two-photon (2p) fluorescence resonance energy transfer (FRET) microscopy, this information can be obtained from living cells and tissues with nanometer resolution. One of the important conditions for FRET to occur is the overlap of the emission spectrum of the donor with the absorption spectrum of the acceptor. As a result of spectral overlap, the FRET signal is always contaminated by donor emission into the acceptor channel and by the excitation of acceptor molecules by the donor excitation wavelength. Mathematical algorithms are required to correct the spectral bleed-through signal in wide-field, confocal, and two-photon FRET microscopy. In contrast, spectral bleed-through is not an issue in FRET/FLIM imaging because only the donor fluorophore lifetime is measured; also, fluorescence lifetime imaging microscopy (FLIM) measurements are independent of excitation intensity or fluorophore concentration. The combination of FRET and FLIM provides high spatial (nanometer) and temporal (nanosecond) resolution when compared to intensity-based FRET imaging. In this paper, we describe various FRET microscopy techniques and its application to protein-protein interactions.     

Imaging living cells and tissues by two-photon excitation microscopy

Two-photon excitation microscopy provides attractive advantages over confocal microscopy for three-dimensionally resolved fluorescence imaging. Since two-photon excitation occurs only at the focal point of the microscope, it inherently provides three-dimensional resolution. This localization of excitation also minimizes photobleaching and photodamage, which are the ultimate limiting factors in imaging living cells. Furthermore, no pinhole is required to attain three-dimensional discrimination, so the efficiency of fluorescence collection is increased. These advantages allow experiments on thick living samples that would not be possible with other imaging techniques. The cost and complexity of the lasers required for two-photon excitation microscopy have limited its use, but appropriate turn-key lasers have now been introduced, and their cost should decrease. Finally, the recent introduction of commercial two-photon excitation laser-scanning microscope systems allows a much larger group of researchers access to this state-of-the-art methodology.     

Visualization and correction of automated segmentation,tracking and lineaging from 5-D stem cell image sequences

Background

Neural stem cells are motile and proliferative cells that undergo mitosis, dividing to produce daughter cells and ultimately generating differentiated neurons and glia. Understanding the mechanisms controlling neural stem cell proliferation and differentiation will play a key role in the emerging fields of regenerative medicine and cancer therapeutics. Stem cell studies in vitro from 2-D image data are well established. Visualizing and analyzing large three dimensional images of intact tissue is a challenging task. It becomes more difficult as the dimensionality of the image data increases to include time and additional fluorescence channels. There is a pressing need for 5-D image analysis and visualization tools to study cellular dynamics in the intact niche and to quantify the role that environmental factors play in determining cell fate.

Results

We present an application that integrates visualization and quantitative analysis of 5-D (x,y,z,t,channel) and large montage confocal fluorescence microscopy images. The image sequences show stem cells together with blood vessels, enabling quantification of the dynamic behaviors of stem cells in relation to their vascular niche, with applications in developmental and cancer biology. Our application automatically segments, tracks, and lineages the image sequence data and then allows the user to view and edit the results of automated algorithms in a stereoscopic 3-D window while simultaneously viewing the stem cell lineage tree in a 2-D window. Using the GPU to store and render the image sequence data enables a hybrid computational approach. An inference-based approach utilizing user-provided edits to automatically correct related mistakes executes interactively on the system CPU while the GPU handles 3-D visualization tasks.

Conclusions

By exploiting commodity computer gaming hardware, we have developed an application that can be run in the laboratory to facilitate rapid iteration through biological experiments. We combine unsupervised image analysis algorithms with an interactive visualization of the results. Our validation interface allows for each data set to be corrected to 100% accuracy, ensuring that downstream data analysis is accurate and verifiable. Our tool is the first to combine all of these aspects, leveraging the synergies obtained by utilizing validation information from stereo visualization to improve the low level image processing tasks.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-328) contains supplementary material, which is available to authorized users.     

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.