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.     

Analyzing cellular internalization of nanoparticles and bacteria by multi-spectral imaging flow cytometry

Nanoparticulate systems have emerged as valuable tools in vaccine delivery through their ability to efficiently deliver cargo, including proteins, to antigen presenting cells. Internalization of nanoparticles (NP) by antigen presenting cells is a critical step in generating an effective immune response to the encapsulated antigen. To determine how changes in nanoparticle formulation impact function, we sought to develop a high throughput, quantitative experimental protocol that was compatible with detecting internalized nanoparticles as well as bacteria. To date, two independent techniques, microscopy and flow cytometry, have been the methods used to study the phagocytosis of nanoparticles. The high throughput nature of flow cytometry generates robust statistical data. However, due to low resolution, it fails to accurately quantify internalized versus cell bound nanoparticles. Microscopy generates images with high spatial resolution; however, it is time consuming and involves small sample sizes. Multi-spectral imaging flow cytometry (MIFC) is a new technology that incorporates aspects of both microscopy and flow cytometry that performs multi-color spectral fluorescence and bright field imaging simultaneously through a laminar core. This capability provides an accurate analysis of fluorescent signal intensities and spatial relationships between different structures and cellular features at high speed. Herein, we describe a method utilizing MIFC to characterize the cell populations that have internalized polyanhydride nanoparticles or Salmonella enterica serovar Typhimurium. We also describe the preparation of nanoparticle suspensions, cell labeling, acquisition on an ImageStream(X) system and analysis of the data using the IDEAS application. We also demonstrate the application of a technique that can be used to differentiate the internalization pathways for nanoparticles and bacteria by using cytochalasin-D as an inhibitor of actin-mediated phagocytosis.     

Cytometry in the brain: studying differentiation to diagnostic applications in brain disease and regeneration therapy

During brain development, a population of uniform embryonic cells migrates and differentiates into a large number of neural phenotypes – origin of the enormous complexity of the adult nervous system. Processes of cell proliferation, differentiation and programmed death of no longer required cells, do not occur only during embryogenesis, but are also maintained during adulthood and are affected in neurodegenerative and neuropsychiatric disease states. As neurogenesis is an endogenous response to brain injury, visible as proliferation (of to this moment silent stem or progenitor cells), its further stimulation can present a treatment strategy in addition to stem cell transfer for cell regeneration therapy. Concise techniques for studying such events in vitro and in vivo permit understanding of underlying mechanisms. Detection of subtle physiological alterations in brain cell proliferation and neurogenesis can be explored, that occur during environmental stimulation, exercise and ageing. Here, we have collected achievements in the field of basic research on applications of cytometry, including automated imaging for quantification of morphological or fluorescence‐based parameters in cell cultures, towards imaging of three‐dimensional brain architecture together with DNA content and proliferation data. Multi‐parameter and more recently in vivo flow cytometry procedures, have been developed for quantification of phenotypic diversity and cell processes that occur during brain development as well as in adulthood, with importance for therapeutic approaches.     

Automated tracking of stem cell lineages of Arabidopsis shoot apex using local graph matching

Shoot apical meristems (SAMs) of higher plants harbor stem‐cell niches. The cells of the stem‐cell niche are organized into spatial domains of distinct function and cell behaviors. A coordinated interplay between cell growth dynamics and changes in gene expression is critical to ensure stem‐cell homeostasis and organ differentiation. Exploring the causal relationships between cell growth patterns and gene expression dynamics requires quantitative methods to analyze cell behaviors from time‐lapse imagery. Although technical breakthroughs in live‐imaging methods have revealed spatio‐temporal dynamics of SAM‐cell growth patterns, robust computational methods for cell segmentation and automated tracking of cells have not been developed. Here we present a local graph matching‐based method for automated‐tracking of cells and cell divisions of SAMs of Arabidopsis thaliana. The cells of the SAM are tightly clustered in space which poses a unique challenge in computing spatio‐temporal correspondences of cells. The local graph‐matching principle efficiently exploits the geometric structure and topology of the relative positions of cells in obtaining spatio‐temporal correspondences. The tracker integrates information across multiple slices in which a cell may be properly imaged, thus providing robustness to cell tracking in noisy live‐imaging datasets. By relying on the local geometry and topology, the method is able to track cells in areas of high curvature such as regions of primordial outgrowth. The cell tracker not only computes the correspondences of cells across spatio‐temporal scale, but it also detects cell division events, and identifies daughter cells upon divisions, thus allowing automated estimation of cell lineages from images captured over a period of 72 h. The method presented here should enable quantitative analysis of cell growth patterns and thus facilitating the development of in silico models for SAM growth.     

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.     

Cellometer image cytometry as a complementary tool to flow cytometry for verifying gated cell populations

Traditionally, many cell-based assays that analyze cell populations and functionalities have been performed using flow cytometry. However, flow cytometers remain relatively expensive and require highly trained operators for routine maintenance and data analysis. Recently, an image cytometry system has been developed by Nexcelom Bioscience (Lawrence, MA, USA) for automated cell concentration and viability measurement using bright-field and fluorescent imaging methods. Image cytometry is analogous to flow cytometry in that gating operations can be performed on the cell population based on size and fluorescent intensity. In addition, the image cytometer is capable of capturing bright-field and fluorescent images, allowing for the measurement of cellular size and fluorescence intensity data. In this study, we labeled a population of cells with an enzymatic vitality stain (calcein-AM) and a cell viability dye (propidium iodide) and compared the data generated by flow and image cytometry. We report that measuring vitality and viability using the image cytometer is as effective as flow cytometric assays and allows for visual confirmation of the sample to exclude cellular debris. Image cytometry offers a direct method for performing fluorescent cell-based assays but also may be used as a complementary tool to flow cytometers for aiding the analysis of more complex samples.     

CycleTrak: a novel system for the semi-automated analysis of cell cycle dynamics

Cell proliferation is crucial to tissue growth and form during embryogenesis, yet dynamic tracking of cell cycle progression and cell position presents a challenging roadblock. We have developed a fluorescent cell cycle indicator and single cell analysis method, called CycleTrak, which allows for better spatiotemporal resolution and quantification of cell cycle phase and cell position than current methods. Our method was developed on the basis of the existing Fucci method. CycleTrak uses a single lentiviral vector that integrates mKO2-hCdt1 (30/120), and a nuclear-localized eGFP reporter. The single vector and nuclear localized fluorescence signals simplify delivery into cells and allow for rapid, automated cell tracking and cell cycle phase readout in single and subpopulations of cells. We validated CycleTrak performance in metastatic melanoma cells and identified novel cell cycle dynamics in vitro and in vivo after transplantation and 3D confocal time-lapse imaging in a living chick embryo.     

When Phase Contrast Fails: ChainTracer and NucTracer,Two ImageJ Methods for Semi-Automated Single Cell Analysis Using Membrane or DNA Staining

Within bacterial populations, genetically identical cells often behave differently. Single-cell measurement methods are required to observe this heterogeneity. Flow cytometry and fluorescence light microscopy are the primary methods to do this. However, flow cytometry requires reasonably strong fluorescence signals and is impractical when bacteria grow in cell chains. Therefore fluorescence light microscopy is often used to measure population heterogeneity in bacteria. Automatic microscopy image analysis programs typically use phase contrast images to identify cells. However, many bacteria divide by forming a cross-wall that is not detectable by phase contrast. We have developed ‘ChainTracer’, a method based on the ImageJ plugin ObjectJ. It can automatically identify individual cells stained by fluorescent membrane dyes, and measure fluorescence intensity, chain length, cell length, and cell diameter. As a complementary analysis method we developed ''NucTracer'', which uses DAPI stained nucleoids as a proxy for single cells. The latter method is especially useful when dealing with crowded images. The methods were tested with Bacillus subtilis and Lactococcus lactis cells expressing a GFP-reporter. In conclusion, ChainTracer and NucTracer are useful single cell measurement methods when bacterial cells are difficult to distinguish with phase contrast.     

Integrating cytomics and proteomics

Systems biology along with what is now classified as cytomics provides an excellent opportunity for cytometry to become integrated into studies where identification of functional proteins in complex cellular mixtures is desired. The combination of cell sorting with rapid protein-profiling platforms offers an automated and rapid technique for greater clarity, accuracy, and efficiency in identification of protein expression differences in mixed cell populations. The integration of cell sorting to purify cell populations opens up a new area for proteomic analysis. This article outlines an approach in which well defined cell analysis and separation tools are integrated into the proteomic programs within a core laboratory. In addition we introduce the concepts of flow cytometry sorting to demonstrate the importance of being able to use flow cytometry as a cell separation technology to identify and collect purified cell populations. Data demonstrating the speed and versatility of this combination of flow cytometry-based cell separation and protein separation and subsequent analysis, examples of protein maps from purified sorted cells, and an analysis of the overall procedure will be shown. It is clear that the power of cell sorting to separate heterogeneous populations of cells using specific phenotypic characteristics increases the power of rapid automated protein separation technologies.     

Quantitative phase imaging of cells in a flow cytometry arrangement utilizing Michelson interferometer‐based off‐axis digital holographic microscopy

We combined Michelson‐interferometer‐based off‐axis digital holographic microscopy (DHM) with a common flow cytometry (FCM) arrangement. Utilizing object recognition procedures and holographic autofocusing during the numerical reconstruction of the acquired off‐axis holograms, sharply focused quantitative phase images of suspended cells in flow were retrieved without labeling, from which biophysical cellular features of distinct cells, such as cell radius, refractive index and dry mass, can be subsequently retrieved in an automated manner. The performance of the proposed concept was first characterized by investigations on microspheres that were utilized as test standards. Then, we analyzed two types of pancreatic tumor cells with different morphology to further verify the applicability of the proposed method for quantitative live cell imaging. The retrieved biophysical datasets from cells in flow are found in good agreement with results from comparative investigations with previously developed DHM methods under static conditions, which demonstrates the effectiveness and reliability of our approach. Our results contribute to the establishment of DHM in imaging FCM and prospect to broaden the application spectrum of FCM by providing complementary quantitative imaging as well as additional biophysical cell parameters which are not accessible in current high‐throughput FCM measurements.     

Synthesis, characterization, and biological properties of cyanine-labeled somatostatin analogues as receptor-targeted fluorescent probes

We present the synthesis and characterization of the somatostatin receptor-specific peptide H(2)N-(D-Phe)-cyclo[Cys-Phe-(D-Trp)-Lys-Thr-Cys]-Thr-OH, which is labeled with a carboxylated indodicarbo- and an indotricarbocyanine dye at the N-terminal amino group. The preparation was performed by automated solid-phase synthesis, with subsequent attachment of the cyanine dye and cleavage of the entire conjugate from the resin. The compounds display high molar absorbance and fluorescence quantum yields typical for cyanine dyes and are thus suitable receptor-targeted contrast agents for molecular optical imaging. The ability of these agents to target the somatostatin receptor was demonstrated by flow cytometry in vitro, in which the indotricarbocyanine conjugate led to elevated cell-associated fluorescence on somatostatin receptor-expressing tumor cells. In contrast, the corresponding linearized derivative of the sequence H(2)N-(D-Phe)-Met-Phe-(D-Trp)-Lys-Thr-Met-Thr-OH produced only minimal cell fluorescence, hence confirming the specificity of the cyclic somatostatin analogue. Intracellular localization could be visualized by near-infrared (NIR) fluorescence microscopy. In conclusion, receptor-specific peptides are promising tools for designing site-directed optical contrast agents for use in molecular optical imaging.     

Combination of quantification and observation methods for study of "Side Population" cells in their "in vitro" microenvironment.

BACKGROUND: Qualitative and quantitative analyses of the rare phenotypic variants in in vitro culture systems is necessary for the understanding of cell differentiation in cell culture of primary cells or cell lines. Slide-based cytometry combines image acquisition and data treatment, and associates the power of flow cytometry (FCM) and the resolution of the microscopic studies making it suitable for the analysis of cells with rare phenotype. In this paper we develop a method that applies these principles to a particularly hot problem in cell biology, the study of stem cell like cells in cultures of primary cells, cancer cells, and various cell lines. METHODS: The adherent cells were labeled by the fluorescent dye Hoechst 33342. The images of cell populations were collected by a two-photon microscope and processed by a software developed by us. The software allows the automated segmentation of the nuclei in a very dense cell environment, the measurement of the fluorescence intensity of each nucleus and the recording of their position in the plate. The cells with a given fluorescence intensity can then be located easily on the recorded image of the culture plate for further analysis. RESULTS: The potential of our method is illustrated by the identification and localization of SP cells in the cultures of the C2C12 cell line. Although these cells represent only about 1% of the total population as calculated by flow cytometry, they can be identified in the culture plate with high precision by microscopy. CONCLUSION: Cells with the rare stem-cell like phenotype can be efficiently identified in the undisturbed cultures. Since the fluorescence intensity of rare events and the position of thousands of surrounding cells are recorded at the same time, the method associates the advantage of the FCM analysis and the microscopic observation.     

Combined confocal and wide-field high-resolution cytometry of fluorescent in situ hybridization-stained cells

BACKGROUND: The recently developed technique of high-resolution cytometry (HRCM) enables automated acquisition and analysis of fluorescent in situ hybridization (FISH)-stained cell nuclei using conventional wide-field fluorescence microscopy. The method has now been extended to confocal imaging and offers the opportunity to combine the advantages of confocal and wide-field modes. METHODS: We have automated image acquisition and analysis from a standard inverted fluorescence microscope equipped with a confocal module with Nipkow disk and a cooled digital CCD camera. The system is fully controlled by a high-performance computer that performs both acquisition and related on-line image analysis. The system can be used either for an automatic two (2D) and three-dimensional (3D) analysis of FISH- stained interphase nuclei or for a semiautomatic 3D analysis of FISH-stained cells in tissues. The user can select which fluorochromes are acquired using wide-field mode and which using confocal mode. The wide-field and confocal images are overlaid automatically in computer memory. The developed software compensates automatically for both chromatic color shifts and spatial shifts caused by switching to a different imaging mode. RESULTS: Using the combined confocal and wide-field HRCM technique, it is possible to take advantage of both imaging modes. Images of some dyes (such as small hybridization dots or counterstain images of individual interphase nuclei) do not require confocal quality and can be acquired quickly in wide-field mode. On the contrary, images of other dyes (such as chromosome territories or counterstain images of cells in tissues) do require improved quality and are acquired in confocal mode. The dual-mode approach is two to three times faster compared with the single-mode confocal approach and the spectrum of its applications is much broader compared with both single-mode confocal and single-mode wide-field systems. CONCLUSIONS: The combination of high speed specific to the wide-field mode and high quality specific to the confocal mode gives optimal system performance.     

Automated quantification of budding Saccharomyces cerevisiae using a novel image cytometry method

The measurements of concentration, viability, and budding percentages of Saccharomyces cerevisiae are performed on a routine basis in the brewing and biofuel industries. Generation of these parameters is of great importance in a manufacturing setting, where they can aid in the estimation of product quality, quantity, and fermentation time of the manufacturing process. Specifically, budding percentages can be used to estimate the reproduction rate of yeast populations, which directly correlates with metabolism of polysaccharides and bioethanol production, and can be monitored to maximize production of bioethanol during fermentation. The traditional method involves manual counting using a hemacytometer, but this is time-consuming and prone to human error. In this study, we developed a novel automated method for the quantification of yeast budding percentages using Cellometer image cytometry. The automated method utilizes a dual-fluorescent nucleic acid dye to specifically stain live cells for imaging analysis of unique morphological characteristics of budding yeast. In addition, cell cycle analysis is performed as an alternative method for budding analysis. We were able to show comparable yeast budding percentages between manual and automated counting, as well as cell cycle analysis. The automated image cytometry method is used to analyze and characterize corn mash samples directly from fermenters during standard fermentation. Since concentration, viability, and budding percentages can be obtained simultaneously, the automated method can be integrated into the fermentation quality assurance protocol, which may improve the quality and efficiency of beer and bioethanol production processes.     

Single cell analysis in biological oceanography and its evolutionary implications

Historically single cell analysis techniques have been usedto supplement more traditional studies of primary production.The techniques have often been used as a surrogate for microscopicanalysis and to close a gap in sea truth coverage for remotesensing and other mapping activities. In the course of developmentfrom Coulter counting to flow cytometry/cell sorting, the instrumentsand techniques have become powerful tools for allometric andataxonomic analysis as well as the quantification of pigmentsand added metabolic stains and tagged reagents. The specificquestions we ask here are: Can flow cytometry-derived data beraised to a level to discern evolutionary direction and diversity/complexity?Can we account for changes in community structure based on allometricand ataxonomic relationships across major ocean boundaries?We present evidence from different approaches and use examplesfrom flow cytometry/cell sorting that address the causes ofvariation in cell size and chlorophyll fluorescence in phytoplankton.The horizon is rapidly expanding yet questions and limitationsof ocean study persist. We believe that a road of commonalityamong oceanographers, ecologists, modelers, microbiologists,molecular biologists, physiologists and paleontologists is needed.     

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.     

Noninvasive photoacoustic and fluorescent tracking of optical dye labeled T cellular activities of diseased sites at new depth

The migration of immune cells is crucial to the immune response. Visualization of these processes has previously been limited because of the imaging depth. We developed a deep‐penetrating, sensitive and high‐resolution method to use fast photoacoustic tomography (PAT) to image the dynamic changes of T cells in lymph node and diseases at new depth (up to 9.5 mm). T cells labeled with NIR‐797‐isothiocyanate, an excellent near‐infrared photoacoustic and fluorescent agent, were intravenously injected to the mice. We used fluorescence imaging to determine the location of T cells roughly and photoacoustic imaging is used to observe T‐cell responses in diseased sites deeply and carefully. The dynamic changes of T cells in lymph node, acute disease (bacterial infection) and chronic disease (tumor) were observed noninvasively by photoacoustic and fluorescence imaging at different time points. T cells accumulated gradually and reached a maximum at 4 hours and declined afterwards in lymph node and bacterial infection site. At tumor model, T cells immigrated to the tumor with a maximum at 12 hours. Our study can not only provide a new observing method for immune activities tracking, but also enable continuous monitoring for therapeutic interventions.      

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.