Imaging of Streptomyces coelicolor A3(2) with Reduced Autofluorescence Reveals a Novel Stage of FtsZ Localization

Imaging of low abundance proteins in time and space by fluorescence microscopy is typically hampered by host-cell autofluorescence. Streptomycetes are an important model system for the study of bacterial development, and undergo multiple synchronous cell division during the sporulation stage. To analyse this phenomenon in detail, fluorescence microscopy, and in particular also the recently published novel live imaging techniques, require optimal signal to noise ratios. Here we describe the development of a novel derivative of Streptomyces coelicolor A3(2) with strongly reduced autofluorescence, allowing the imaging of fluorescently labelled proteins at significantly higher resolution. The enhanced image detail provided novel localization information for the cell division protein FtsZ, demonstrating a new developmental stage where multiple FtsZ foci accumulate at the septal plane. This suggests that multiple foci are sequentially produced, ultimately connecting to form the complete Z ring. The enhanced imaging properties are an important step forward for the confocal and live imaging of less abundant proteins and for the use of lower intensity fluorophores in streptomycetes.     

Deep Imaging: the next frontier in microscopy

The microscope is the quintessential tool for discovery in cell biology. From its earliest incarnation as a tool to make the unseen visible, microscopes have been at the center of most revolutionizing developments in cell biology, histology and pathology. Major quantum leaps in imaging involved the dramatic improvements in resolution to see increasingly smaller structures, methods to visualize specific molecules inside of cells and tissues, and the ability to peer into living cells to study dynamics of molecules and cellular structures. The latest revolution in microscopy is Deep Imaging—the ability to look at very large numbers of samples by high-throughput microscopy at high spatial and temporal resolution. This approach is rooted in the development of fully automated high-resolution microscopes and the application of advanced computational image analysis and mining methods. Deep Imaging is enabling two novel, powerful approaches in cell biology: the ability to image thousands of samples with high optical precision allows every discernible morphological pattern to be used as a read-out in large-scale imaging-based screens, particularly in conjunction with RNAi-based screening technology; in addition, the capacity to capture large numbers of images, combined with advanced computational image analysis methods, has also opened the door to detect and analyze very rare cellular events. These two applications of Deep Imaging are revolutionizing cell biology.     

Characterization of Cell Boundary and Confocal Effects Improves Quantitative FRAP Analysis

Fluorescence recovery after photobleaching (FRAP) is an important tool used by cell biologists to study the diffusion and binding kinetics of vesicles, proteins, and other molecules in the cytoplasm, nucleus, or cell membrane. Although many FRAP models have been developed over the past decades, the influence of the complex boundaries of 3D cellular geometries on the recovery curves, in conjunction with regions of interest and optical effects (imaging, photobleaching, photoswitching, and scanning), has not been well studied. Here, we developed a 3D computational model of the FRAP process that incorporates particle diffusion, cell boundary effects, and the optical properties of the scanning confocal microscope, and validated this model using the tip-growing cells of Physcomitrella patens. We then show how these cell boundary and optical effects confound the interpretation of FRAP recovery curves, including the number of dynamic states of a given fluorophore, in a wide range of cellular geometries—both in two and three dimensions—namely nuclei, filopodia, and lamellipodia of mammalian cells, and in cell types such as the budding yeast, Saccharomyces pombe, and tip-growing plant cells. We explored the performance of existing analytical and algorithmic FRAP models in these various cellular geometries, and determined that the VCell VirtualFRAP tool provides the best accuracy to measure diffusion coefficients. Our computational model is not limited only to these cells types, but can easily be extended to other cellular geometries via the graphical Java-based application we also provide. This particle-based simulation—called the Digital Confocal Microscopy Suite or DCMS—can also perform fluorescence dynamics assays, such as number and brightness, fluorescence correlation spectroscopy, and raster image correlation spectroscopy, and could help shape the way these techniques are interpreted.     

Harnessing Single Cell Sorting to Identify Cell Division Genes and Regulators in Bacteria

Cell division is an essential cellular process that requires an array of known and unknown proteins for its spatial and temporal regulation. Here we develop a novel, high-throughput screening method for the identification of bacterial cell division genes and regulators. The method combines the over-expression of a shotgun genomic expression library to perturb the cell division process with high-throughput flow cytometry sorting to screen many thousands of clones. Using this approach, we recovered clones with a filamentous morphology for the model bacterium, Escherichia coli. Genetic analysis revealed that our screen identified both known cell division genes, and genes that have not previously been identified to be involved in cell division. This novel screening strategy is applicable to a wide range of organisms, including pathogenic bacteria, where cell division genes and regulators are attractive drug targets for antibiotic development.     

Long-Term Live Cell Imaging and Automated 4D Analysis of Drosophila Neuroblast Lineages

The developing Drosophila brain is a well-studied model system for neurogenesis and stem cell biology. In the Drosophila central brain, around 200 neural stem cells called neuroblasts undergo repeated rounds of asymmetric cell division. These divisions typically generate a larger self-renewing neuroblast and a smaller ganglion mother cell that undergoes one terminal division to create two differentiating neurons. Although single mitotic divisions of neuroblasts can easily be imaged in real time, the lack of long term imaging procedures has limited the use of neuroblast live imaging for lineage analysis. Here we describe a method that allows live imaging of cultured Drosophila neuroblasts over multiple cell cycles for up to 24 hours. We describe a 4D image analysis protocol that can be used to extract cell cycle times and growth rates from the resulting movies in an automated manner. We use it to perform lineage analysis in type II neuroblasts where clonal analysis has indicated the presence of a transit-amplifying population that potentiates the number of neurons. Indeed, our experiments verify type II lineages and provide quantitative parameters for all cell types in those lineages. As defects in type II neuroblast lineages can result in brain tumor formation, our lineage analysis method will allow more detailed and quantitative analysis of tumorigenesis and asymmetric cell division in the Drosophila brain.     

Dynamics of Snake-like Swarming Behavior of Vibrio alginolyticus

Swarming represents a special case of bacterial behavior where motile bacteria migrate rapidly and collectively on surfaces. Swarming and swimming motility of bacteria has been studied well for rigid, self-propelled rods. In this study we report a strain of Vibrio alginolyticus, a species that exhibits similar collective motility but a fundamentally different cell morphology with highly flexible snake-like swarming cells. Investigating swarming dynamics requires high-resolution imaging of single cells with coverage over a large area: thousands of square microns. Researchers previously have employed various methods of motion analysis but largely for rod-like bacteria. We employ temporal variance analysis of a short time-lapse microscopic image series to capture the motion dynamics of swarming Vibrio alginolyticus at cellular resolution over hundreds of microns. Temporal variance is a simple and broadly applicable method for analyzing bacterial swarming behavior in two and three dimensions with both high-resolution and wide-spatial coverage. This study provides detailed insights into the swarming architecture and dynamics of Vibrio alginolyticus isolate B522 on carrageenan agar that may lay the foundation for swarming studies of snake-like, nonrod-shaped motile cell types.     

Videomicroscopic extraction of specific information on cell proliferation and migration in vitro

In vitro cell imaging is a useful exploratory tool for cell behavior monitoring with a wide range of applications in cell biology and pharmacology. Combined with appropriate image analysis techniques, this approach has been shown to provide useful information on the detection and dynamic analysis of cell events. In this context, numerous efforts have been focused on cell migration analysis. In contrast, the cell division process has been the subject of fewer investigations. The present work focuses on this latter aspect and shows that, in complement to cell migration data, interesting information related to cell division can be extracted from phase-contrast time-lapse image series, in particular cell division duration, which is not provided by standard cell assays using endpoint analyses. We illustrate our approach by analyzing the effects induced by two sigma-1 receptor ligands (haloperidol and 4-IBP) on the behavior of two glioma cell lines using two in vitro cell models, i.e., the low-density individual cell model and the high-density scratch wound model. This illustration also shows that the data provided by our approach are suggestive as to the mechanism of action of compounds, and are thus capable of informing the appropriate selection of further time-consuming and more expensive biological evaluations required to elucidate a mechanism.     

Modeling cellular processes in 3D

Recent advances in photonic imaging and fluorescent protein technology offer unprecedented views of molecular space-time dynamics in living cells. At the same time, advances in computing hardware and software enable modeling of ever more complex systems, from global climate to cell division. As modeling and experiment become more closely integrated we must address the issue of modeling cellular processes in 3D. Here, we highlight recent advances related to 3D modeling in cell biology. While some processes require full 3D analysis, we suggest that others are more naturally described in 2D or 1D. Keeping the dimensionality as low as possible reduces computational time and makes models more intuitively comprehensible; however, the ability to test full 3D models will build greater confidence in models generally and remains an important emerging area of cell biological modeling.     

Long‐term live‐cell imaging reveals new roles for Salmonella effector proteins SseG and SteA

Salmonella Typhimurium is an intracellular bacterial pathogen that infects both epithelial cells and macrophages. Salmonella effector proteins, which are translocated into the host cell and manipulate host cell components, control the ability to replicate and/or survive in host cells. Due to the complexity and heterogeneity of Salmonella infections, there is growing recognition of the need for single‐cell and live‐cell imaging approaches to identify and characterize the diversity of cellular phenotypes and how they evolve over time. Here, we establish a pipeline for long‐term (17 h) live‐cell imaging of infected cells and subsequent image analysis methods. We apply this pipeline to track bacterial replication within the Salmonella‐containing vacuole in epithelial cells, quantify vacuolar replication versus survival in macrophages and investigate the role of individual effector proteins in mediating these parameters. This approach revealed that dispersed bacteria can coalesce at later stages of infection, that the effector protein SseG influences the propensity for cytosolic hyper‐replication in epithelial cells, and that while SteA only has a subtle effect on vacuolar replication in epithelial cells, it has a profound impact on infection parameters in immunocompetent macrophages, suggesting differential roles for effector proteins in different infection models.     

Polarized Cell Division of Chlamydia trachomatis

Bacterial cell division predominantly occurs by a highly conserved process, termed binary fission, that requires the bacterial homologue of tubulin, FtsZ. Other mechanisms of bacterial cell division that are independent of FtsZ are rare. Although the obligate intracellular human pathogen Chlamydia trachomatis, the leading bacterial cause of sexually transmitted infections and trachoma, lacks FtsZ, it has been assumed to divide by binary fission. We show here that Chlamydia divides by a polarized cell division process similar to the budding process of a subset of the Planctomycetes that also lack FtsZ. Prior to cell division, the major outer-membrane protein of Chlamydia is restricted to one pole of the cell, and the nascent daughter cell emerges from this pole by an asymmetric expansion of the membrane. Components of the chlamydial cell division machinery accumulate at the site of polar growth prior to the initiation of asymmetric membrane expansion and inhibitors that disrupt the polarity of C. trachomatis prevent cell division. The polarized cell division of C. trachomatis is the result of the unipolar growth and FtsZ-independent fission of this coccoid organism. This mechanism of cell division has not been documented in other human bacterial pathogens suggesting the potential for developing Chlamydia-specific therapeutic treatments.     

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.     

A Multi-layered Protein Network Stabilizes the Escherichia coli FtsZ-ring and Modulates Constriction Dynamics

The prokaryotic tubulin homolog, FtsZ, forms a ring-like structure (FtsZ-ring) at midcell. The FtsZ-ring establishes the division plane and enables the assembly of the macromolecular division machinery (divisome). Although many molecular components of the divisome have been identified and their interactions extensively characterized, the spatial organization of these proteins within the divisome is unclear. Consequently, the physical mechanisms that drive divisome assembly, maintenance, and constriction remain elusive. Here we applied single-molecule based superresolution imaging, combined with genetic and biophysical investigations, to reveal the spatial organization of cellular structures formed by four important divisome proteins in E. coli: FtsZ, ZapA, ZapB and MatP. We show that these interacting proteins are arranged into a multi-layered protein network extending from the cell membrane to the chromosome, each with unique structural and dynamic properties. Further, we find that this protein network stabilizes the FtsZ-ring, and unexpectedly, slows down cell constriction, suggesting a new, unrecognized role for this network in bacterial cell division. Our results provide new insight into the structure and function of the divisome, and highlight the importance of coordinated cell constriction and chromosome segregation.     

Super-Resolution Imaging Strategies for Cell Biologists Using a Spinning Disk Microscope

In this study we use a spinning disk confocal microscope (SD) to generate super-resolution images of multiple cellular features from any plane in the cell. We obtain super-resolution images by using stochastic intensity fluctuations of biological probes, combining Photoactivation Light-Microscopy (PALM)/Stochastic Optical Reconstruction Microscopy (STORM) methodologies. We compared different image analysis algorithms for processing super-resolution data to identify the most suitable for analysis of particular cell structures. SOFI was chosen for X and Y and was able to achieve a resolution of ca. 80 nm; however higher resolution was possible >30 nm, dependant on the super-resolution image analysis algorithm used. Our method uses low laser power and fluorescent probes which are available either commercially or through the scientific community, and therefore it is gentle enough for biological imaging. Through comparative studies with structured illumination microscopy (SIM) and widefield epifluorescence imaging we identified that our methodology was advantageous for imaging cellular structures which are not immediately at the cell-substrate interface, which include the nuclear architecture and mitochondria. We have shown that it was possible to obtain two coloured images, which highlights the potential this technique has for high-content screening, imaging of multiple epitopes and live cell imaging.     

Accurate Automatic Detection of Densely Distributed Cell Nuclei in 3D Space

To measure the activity of neurons using whole-brain activity imaging, precise detection of each neuron or its nucleus is required. In the head region of the nematode C. elegans, the neuronal cell bodies are distributed densely in three-dimensional (3D) space. However, no existing computational methods of image analysis can separate them with sufficient accuracy. Here we propose a highly accurate segmentation method based on the curvatures of the iso-intensity surfaces. To obtain accurate positions of nuclei, we also developed a new procedure for least squares fitting with a Gaussian mixture model. Combining these methods enables accurate detection of densely distributed cell nuclei in a 3D space. The proposed method was implemented as a graphical user interface program that allows visualization and correction of the results of automatic detection. Additionally, the proposed method was applied to time-lapse 3D calcium imaging data, and most of the nuclei in the images were successfully tracked and measured.     

Mass spectrometry imaging with high resolution in mass and space

Mass spectrometry (MS) imaging links molecular information and the spatial distribution of analytes within a sample. In contrast to most histochemical techniques, mass spectrometry imaging can differentiate molecular modifications and does not require labeling of targeted compounds. We have recently introduced the first mass spectrometry imaging method that provides highly specific molecular information (high resolution and accuracy in mass) at cellular dimensions (high resolution in space). This method is based on a matrix-assisted laser desorption/ionization (MALDI) imaging source working at atmospheric pressure which is coupled to an orbital trapping mass spectrometer. Here, we present a number of application examples and demonstrate the benefit of ‘mass spectrometry imaging with high resolution in mass and space.’ Phospholipids, peptides and drug compounds were imaged in a number of tissue samples at a spatial resolution of 5–10 μm. Proteins were analyzed after on-tissue tryptic digestion at 50-μm resolution. Additional applications include the analysis of single cells and of human lung carcinoma tissue as well as the first MALDI imaging measurement of tissue at 3 μm pixel size. MS image analysis for all these experiments showed excellent correlation with histological staining evaluation. The high mass resolution (R = 30,000) and mass accuracy (typically 1 ppm) proved to be essential for specific image generation and reliable identification of analytes in tissue samples. The ability to combine the required high-quality mass analysis with spatial resolution in the range of single cells is a unique feature of our method. With that, it has the potential to supplement classical histochemical protocols and to provide new insights about molecular processes on the cellular level.     

Advances in using MRI probes and sensors for in vivo cell tracking as applied to regenerative medicine

The field of molecular and cellular imaging allows molecules and cells to be visualized in vivo non-invasively. It has uses not only as a research tool but in clinical settings as well, for example in monitoring cell-based regenerative therapies, in which cells are transplanted to replace degenerating or damaged tissues, or to restore a physiological function. The success of such cell-based therapies depends on several critical issues, including the route and accuracy of cell transplantation, the fate of cells after transplantation, and the interaction of engrafted cells with the host microenvironment. To assess these issues, it is necessary to monitor transplanted cells non-invasively in real-time. Magnetic resonance imaging (MRI) is a tool uniquely suited to this task, given its ability to image deep inside tissue with high temporal resolution and sensitivity. Extraordinary efforts have recently been made to improve cellular MRI as applied to regenerative medicine, by developing more advanced contrast agents for use as probes and sensors. These advances enable the non-invasive monitoring of cell fate and, more recently, that of the different cellular functions of living cells, such as their enzymatic activity and gene expression, as well as their time point of cell death. We present here a review of recent advancements in the development of these probes and sensors, and of their functioning, applications and limitations.KEY WORDS: Regenerative medicine, Stem cells, Magnetic resonance imaging, Paramagnetic contrast agents, CEST, Perfluorocarbon particles, Biosensor, Cell labeling, Cellular function     

Extracting meaning from biological imaging data

Biological imaging continues to improve, capturing continually longer-term, richer, and more complex data, penetrating deeper into live tissue. How do we gain insight into the dynamic processes of disease and development from terabytes of multidimensional image data? Here I describe a collaborative approach to extracting meaning from biological imaging data. The collaboration consists of teams of biologists and engineers working together. Custom computational tools are built to best exploit application-specific knowledge in order to visualize and analyze large and complex data sets. The image data are summarized, extracting and modeling the features that capture the objects and relationships in the data. The summarization is validated, the results visualized, and errors corrected as needed. Finally, the customized analysis and visualization tools together with the image data and the summarization results are shared. This Perspective provides a brief guide to the mathematical ideas that rigorously quantify the notion of extracting meaning from biological image, and to the practical approaches that have been used to apply these ideas to a wide range of applications in cell and tissue optical imaging.     

A novel encoded particle technology that enables simultaneous interrogation of multiple cell types

The authors have developed a cellular analysis platform, based on encoded microcarriers, that enables the multiplexed analysis of a diverse range of cellular assays. At the core of this technology are classes of microcarriers that have unique, identifiable codes that are deciphered using CCD-based imaging and subsequent image analysis. The platform is compatible with a wide variety of cellular imaging-based assays, including calcium flux, reporter gene activation, cytotoxicity, and proliferation. In addition, the platform is compatible with both colorimetric and fluorescent readouts. Notably, this technology has the unique ability to multiplex different cell lines in a single microplate well, enabling scientists to perform assays and data analysis in novel ways.