To 5D and beyond: quantitative fluorescence microscopy in the postgenomic era

Efficient simulation of autofluorescence effects in microscope lenses

The use of fluorescence in microscopy is a well-known technology. Due to autofluorescence in the materials of optical components, the contrast of the image is degraded. The calculation of autofluorescence is usually performed by brute-force methods such as the Monte Carlo-based volume scattering. The efficiency of calculations in this case is extremely low, and a huge number of rays must be calculated. In stray light calculations, the concept of important sampling is used to reduce computational effort. The idea is to calculate only rays, which have the chance to reach the target surface. The fluorescence conversion can be considered to be a scatter process, and therefore a modification of this idea is used here. The reduction factor is calculated by comparing the size of the illuminated phase space domain with the corresponding acceptance domain in every z plane of the lenses. The boundaries of the domains are determined by tracing the limiting rays of the light cone of the source as well as the pixel area under consideration. The small overlap of both domains can be estimated by geometrical considerations. The correct photometric scaling and the discretization of the volumes must be performed. The errors resulting from necessary approximations can be corrected without greatly increasing computational effort. The run time is reduced by a factor of 10⁴. It is shown with some practical examples of microscope lenses that the results are comparable with conventional methods. Additionally, a quasi-analytical model that describes the dependence of autofluorescence on various lens parameters is derived.

Observing Mitotic Division and Dynamics in a Live Zebrafish Embryo

Mitosis is critical for organismal growth and differentiation. The process is highly dynamic and requires ordered events to accomplish proper chromatin condensation, microtubule-kinetochore attachment, chromosome segregation, and cytokinesis in a small time frame. Errors in the delicate process can result in human disease, including birth defects and cancer. Traditional approaches investigating human mitotic disease states often rely on cell culture systems, which lack the natural physiology and developmental/tissue-specific context advantageous when studying human disease. This protocol overcomes many obstacles by providing a way to visualize, with high resolution, chromosome dynamics in a vertebrate system, the zebrafish. This protocol will detail an approach that can be used to obtain dynamic images of dividing cells, which include: in vitro transcription, zebrafish breeding/collecting, embryo embedding, and time-lapse imaging. Optimization and modifications of this protocol are also explored. Using H2A.F/Z-EGFP (labels chromatin) and mCherry-CAAX (labels cell membrane) mRNA-injected embryos, mitosis in AB wild-type, auroraB(hi1045) (,) and esco2(hi2865) mutant zebrafish is visualized. High resolution live imaging in zebrafish allows one to observe multiple mitoses to statistically quantify mitotic defects and timing of mitotic progression. In addition, observation of qualitative aspects that define improper mitotic processes (i.e., congression defects, missegregation of chromosomes, etc.) and improper chromosomal outcomes (i.e., aneuploidy, polyploidy, micronuclei, etc.) are observed. This assay can be applied to the observation of tissue differentiation/development and is amenable to the use of mutant zebrafish and pharmacological agents. Visualization of how defects in mitosis lead to cancer and developmental disorders will greatly enhance understanding of the pathogenesis of disease.

Metadata management for high content screening in OMERO

High content screening (HCS) experiments create a classic data management challenge-multiple, large sets of heterogeneous structured and unstructured data, that must be integrated and linked to produce a set of "final" results. These different data include images, reagents, protocols, analytic output, and phenotypes, all of which must be stored, linked and made accessible for users, scientists, collaborators and where appropriate the wider community. The OME Consortium has built several open source tools for managing, linking and sharing these different types of data. The OME Data Model is a metadata specification that supports the image data and metadata recorded in HCS experiments. Bio-Formats is a Java library that reads recorded image data and metadata and includes support for several HCS screening systems. OMERO is an enterprise data management application that integrates image data, experimental and analytic metadata and makes them accessible for visualization, mining, sharing and downstream analysis. We discuss how Bio-Formats and OMERO handle these different data types, and how they can be used to integrate, link and share HCS experiments in facilities and public data repositories. OME specifications and software are open source and are available at https://www.openmicroscopy.org.

Publishing and sharing multi-dimensional image data with OMERO

Imaging data are used in the life and biomedical sciences to measure the molecular and structural composition and dynamics of cells, tissues, and organisms. Datasets range in size from megabytes to terabytes and usually contain a combination of binary pixel data and metadata that describe the acquisition process and any derived results. The OMERO image data management platform allows users to securely share image datasets according to specific permissions levels: data can be held privately, shared with a set of colleagues, or made available via a public URL. Users control access by assigning data to specific Groups with defined membership and access rights. OMERO’s Permission system supports simple data sharing in a lab, collaborative data analysis, and even teaching environments. OMERO software is open source and released by the OME Consortium at www.openmicroscopy.org.

3D restoration microscopy improves quantification of enzyme-labeled fluorescence-based single-cell phosphatase activity in plankton

The ELF or fluorescence-labeled enzyme activity (FLEA) technique is a culture-independent single-cell tool for assessing plankton enzyme activity in close-to-in situ conditions. We demonstrate that single-cell FLEA quantifications based on two-dimensional (2D) image analysis were biased by up to one order of magnitude relative to deconvolved 3D. This was basically attributed to out-of-focus light, and partially to object size. Nevertheless, if sufficient cells were measured (25-40 cells), biases in individual 2D cell measurements were partially compensated, providing useful and comparable results to deconvolved 3D. We also discuss how much caution should be used when comparing the single-cell enzyme activities of different sized bacterio- and/or phytoplankton populations measured on 2D images. Finally, a novel method based on deconvolved 3D images (wide field restoration microscopy; WFR) was devised to improve the discrimination of similar single-cell enzyme activities, the comparison of enzyme activities between different size cells, the measurement of low fluorescence intensities, the quantification of less numerous species, and the combination of the FLEA technique with other single-cell methods. These improvements in cell enzyme activity measurements will provide a more precise picture of individual species' behavior in nature, which is essential to understand their functional role and evolutionary history.

Bridging the gap between qualitative and quantitative colocalization results in fluorescence microscopy studies

Quantitative colocalization studies suffer from the lack of unified approach to interpret obtained results. We developed a tool to characterize the results of colocalization experiments in a way so that they are understandable and comparable both qualitatively and quantitatively. Employing a fuzzy system model and computer simulation, we produced a set of just five linguistic variables tied to the values of popular colocalization coefficients: “Very Weak”, “Weak”, “Moderate”, “Strong”, and “Very Strong”. The use of the variables ensures that the results of colocalization studies are properly reported, easily shared, and universally understood by all researchers working in the field. When new coefficients are introduced, their values can be readily fitted into the set.

3D/4D functional imaging of tumor-associated proteolysis: impact of microenvironment

Proteases play causal roles in many aspects of the aggressive phenotype of tumors, yet many of the implicated proteases originate from tumor-associated cells or from responses of tumor cells to interactions with other cells. Therefore, to obtain a comprehensive view of tumor proteases, we need to be able to assess proteolysis in tumors that are interacting with their microenvironment. As this is difficult to do in vivo, we have developed functional live-cell optical imaging assays and 3D and 4D (i.e., 3D over time) coculture models. We present here a description of the probes used to measure proteolysis and protease activities, the methods used for imaging and analysis of proteolysis and the 3D and 4D models used in our laboratory. Of course, all assays have limitations; however, we suggest that the techniques discussed here will, with attention to their limitations, be useful as a screen for drugs to target the invasive phenotype of tumors.

Single molecule experimentation in biological physics: exploring the living component of soft condensed matter one molecule at a time

The soft matter of biological systems consists of mesoscopic length scale building blocks, composed of a variety of different types of biological molecules. Most single biological molecules are so small that 1 billion would fit on the full-stop at the end of this sentence, but collectively they carry out the vital activities in living cells whose length scale is at least three orders of magnitude greater. Typically, the number of molecules involved in any given cellular process at any one time is relatively small, and so real physiological events may often be dominated by stochastics and fluctuation behaviour at levels comparable to thermal noise, and are generally heterogeneous in nature. This challenging combination of heterogeneity and stochasticity is best investigated experimentally at the level of single molecules, as opposed to more conventional bulk ensemble-average techniques. In recent years, the use of such molecular experimental approaches has become significantly more widespread in research laboratories around the world. In this review we discuss recent experimental approaches in biological physics which can be applied to investigate the living component of soft condensed matter to a precision of a single molecule.

Method of calibration of a fluorescence microscope for quantitative studies

Confocal microscopy is based on measurement of intensity of fluorescence originating from a limited volume in the imaged specimen. The intensity is quantized in absolute (albeit arbitrary) units, producing a digital 3D micrograph. Thus, one may obtain quantitative information on local concentration of biomolecules in cells and tissues. This approach requires estimation of precision of light measurement (limited by noise) and conversion of the digital intensity units to absolute values of concentration (or number) of molecules of interest. To meet the first prerequisite we propose a technique for measurement of signal and noise. This method involves registration of a time series of images of any stationary microscope specimen. The analysis is a multistep process, which separates monotonic, periodic and random components of pixel intensity change. This approach permits simultaneous determination of dark and photonic components of noise. Consequently, confidence interval (total noise estimation) is obtained for every level of signal. The algorithm can also be applied to detect mechanical instability of a microscope and instability of illumination source. The presented technique is combined with a simple intensity standard to provide conversion of relative intensity units into their absolute counterparts (the second prerequisite of quantitative imaging). Moreover, photobleaching kinetics of the standard is used to estimate the power of light delivered to a microscope specimen. Thus, the proposed method provides in one step an absolute intensity calibration, estimate of precision and sensitivity of a microscope system.

Bisque: a platform for bioimage analysis and management

MOTIVATION

Advances in the field of microscopy have brought about the need for better image management and analysis solutions. Novel imaging techniques have created vast stores of images and metadata that are difficult to organize, search, process and analyze. These tasks are further complicated by conflicting and proprietary image and metadata formats, that impede analyzing and sharing of images and any associated data. These obstacles have resulted in research resources being locked away in digital media and file cabinets. Current image management systems do not address the pressing needs of researchers who must quantify image data on a regular basis.

RESULTS

We present Bisque, a web-based platform specifically designed to provide researchers with organizational and quantitative analysis tools for 5D image data. Users can extend Bisque with both data model and analysis extensions in order to adapt the system to local needs. Bisque's extensibility stems from two core concepts: flexible metadata facility and an open web-based architecture. Together these empower researchers to create, develop and share novel bioimage analyses. Several case studies using Bisque with specific applications are presented as an indication of how users can expect to extend Bisque for their own purposes.

In vivo imaging of mammalian cells: image acquisition and analysis

Live cell imaging provides a powerful technique for the analysis of molecular dynamics within cells. Advances in imaging technology and probe design have established this approach as an important tool in modern biology. It is now possible to obtain commercial turnkey systems for digital imaging using a number of different imaging modalities. Nevertheless, it still requires considerable technical care and expertise to conduct a successful experiment. To perform a successful imaging experiment, it is important to maximize the signal-to-noise ratio (S:N) while minimizing damage to the cells. In this article, we focus on the use of fluorescence microscopy in live cell imaging, although most of the points discussed are relevant to any type of imaging. We describe many of the methods and considerations that are required for performing a successful imaging experiment in living cells. However, we do not provide a single recipe for success: The approach is much too empirical and depends on careful observation of the particular cells under investigation.

A novel assay based on fluorescence microscopy and image processing for determining phenotypic distributions of rod-shaped bacteria

Cell population balance (CPB) models can account for the phenotypic heterogeneity that characterizes isogenic cell populations. To utilize the predictive power of these models, however, we must determine the single-cell reaction and division rates as well as the partition probability density function of the cell population. These functions can be obtained through the Collins-Richmond inverse CPB modeling methodology, if we know the phenotypic distributions of (a) the overall cell population, (b) the dividing cell subpopulation, and (c) the newborn cell subpopulation. This study presents the development of a novel assay that combines fluorescence microscopy and image processing to determine these distributions. The method is generally applicable to rod-shaped cells dividing through the formation of a characteristic constriction. Morphological criteria were developed for the automatic identification of dividing cells and validated through direct comparison with manually obtained measurements. The newborn cell subpopulation was obtained from the corresponding dividing cell subpopulation by collecting information from the two compartments separated by the constriction. The method was applied to E. coli cells carrying the genetic toggle network with a green fluorescent marker. Our measurements for the overall cell population were in excellent agreement with the distributions obtained via flow cytometry. The new assay constitutes a powerful tool that can be used in conjunction with inverse CPB modeling to rigorously quantify single-cell behavior from data collected from highly heterogeneous cell populations.

Bioimage informatics for experimental biology

Over the past twenty years there have been great advances in light microscopy with the result that multidimensional imaging has driven a revolution in modern biology. The development of new approaches of data acquisition is reported frequently, and yet the significant data management and analysis challenges presented by these new complex datasets remain largely unsolved. As in the well-developed field of genome bioinformatics, central repositories are and will be key resources, but there is a critical need for informatics tools in individual laboratories to help manage, share, visualize, and analyze image data. In this article we present the recent efforts by the bioimage informatics community to tackle these challenges, and discuss our own vision for future development of bioimage informatics solutions.

Over the rainbow: 25 years of confocal imaging

Confocal microscopes have evolved over the past 25 years from the early stage scanning systems to a collection of sophisticated laser scanning systems designed for a range of biomedical applications. Major improvements to the photon efficiency of the instrumentation coupled with the development of novel fluorescent reporters have enabled multidimensional imaging of living cells and tissues.

Optical protein sensor for detecting cancer markers in saliva

A surface immobilized optical protein sensor has been utilized to detect Interleukin-8 (IL-8) protein, an oral cancer marker, and can reach limit of detection (LOD) at 1.1 pM in buffer without using enzymatic amplification. Only after applying enzymatic amplification to increase the signal level by a few orders of magnitude, ELISA can reach the LOD of 1 pM level. We then develop the confocal optics based sensor for further reducing the optical noise and can extend the LOD of the surface immobilized optical protein sensor two orders in magnitude. These improvements have allowed us to detect IL-8 protein at 4.0 fM in buffer. In addition, these sensitive LODs were achieved without the use of enzymatic signal amplification, such that the simplified protocol can further facilitate the development of point-of-care devices. The ultra sensitive optical protein sensor presented in this paper has a wide number of applications in disease diagnoses. Measurements for detecting biomarkers in clinical sample are much more challenging than the measurements in buffer, due to high background noise contributed by large collections of non-target molecules. We used clinical saliva samples to validate the functionality of the optical protein sensor. Clinical detection of disease-specific biomarkers in saliva offers a non-invasive, alternative approach to using blood or urine. Currently, the main challenge of using saliva as a diagnostic fluid is its inherently low concentration of biomarkers. We compare the measurements of 40 saliva samples; half from oral cancer patients and half from a control group. The data measured by the optical protein sensor is compared with the traditional Enzyme-Linked Immunosorbant Assay (ELISA) values to validate the accuracy of our system. These positive results enable us to proceed to using confocal optical protein sensor to detect other biomarkers, which have much lower concentrations.

Precision of light intensity measurement in biological optical microscopy

Standardization and calibration of optical microscopy systems have become an important issue owing to the increasing role of biological imaging in high-content screening technology. The proper interpretation of data from high-content screening imaging experiments requires detailed information about the capabilities of the systems, including their available dynamic range, sensitivity and noise. Currently available techniques for calibration and standardization of digital microscopes commonly used in cell biology laboratories provide an estimation of stability and measurement precision (noise) of an imaging system at a single level of signal intensity. In addition, only the total noise level, not its characteristics (spectrum), is measured. We propose a novel technique for estimation of temporal variability of signal and noise in microscopic imaging. The method requires registration of a time series of images of any stationary biological specimen. The subsequent analysis involves a multi-step process, which separates monotonic, periodic and random components of every pixel intensity change in time. The technique allows simultaneous determination of dark, photonic and multiplicative components of noise present in biological measurements. Consequently, a respective confidence interval (noise level) is obtained for each level of signal. The technique is validated using test sets of biological images with known signal and noise characteristics. The method is also applied to assess uncertainty of measurement obtained with two CCD cameras in a wide-field microscope.

Modelling data across labs, genomes, space and time

Logical models and physical specifications provide the foundation for storage, management and analysis of complex sets of data, and describe the relationships between measured data elements and metadata - the contextual descriptors that define the primary data. Here, we use imaging applications to illustrate the purpose of the various implementations of data specifications and the requirement for open, standardized, data formats to facilitate the sharing of critical digital data and metadata.

Open microscopy environment and findspots: integrating image informatics with quantitative multidimensional image analysis

Biomedical research and drug development increasingly involve the extraction of quantitative data from digital microscope images, such as those obtained using fluorescence microscopy. Here, we describe a novel approach for both managing and analyzing such images. The Open Microscopy Environment (OME) is a sophisticated open-source scientific image management database that coordinates the organization, storage, and analysis of the large volumes of image data typically generated by modern imaging methods. We describe FindSpots, a powerful image-analysis package integrated in OME that will be of use to those who wish to identify and measure objects within microscope images or time-lapse movies. The algorithm used in FindSpots is in fact only one of many possible segmentation (object detection) algorithms, and the underlying data model used by OME to capture and store its results can also be used to store results from other segmentation algorithms. In this report, we illustrate how image segmentation can be achieved in OME using one such implementation of a segmentation algorithm, and how this output subsequently can be displayed graphically or processed numerically using a spreadsheet.

Extracting quantitative information from tissue--an industrial perspective

The focus of this article is to provide an overview of the current technologies for the pharmaceutical and biotech industry. Disease processes express themselves in the functional and structural disturbance of cellular systems. Cells and their metabolites constitute the building blocks of tissues and entire organisms. Studying the spatial and temporal phenotype of disease processes in tissues at the cellular level reveals a multitude of information about the progress and status of a disease. Detailed exploration of tissues by slide-based cytometry is an important source of information about disease processes. Technological and analytical advances allow us to shed a new light on tissues and to come to a better understanding of the complexity of disease processes. Dealing with complex multidimensional datasets from tissue samples requires an advanced approach to image processing and data management. The increase in computing power and the continuing research into imaging algorithms allow us to improve the exploration of the data content of tissues.

Cytomics and drug discovery

Pharmaceutical companies try to develop new drugs that have a high success rate of reaching the market. However, current disease models lack a strong correlation to clinical reality, because of the underestimation of the complexity and variability of clinical disease processes. This leads to high attrition rates late in drug development and soaring costs. Improvement of disease models is an important issue to reduce the high attrition rates in drug development. Using cell-based disease models, which should take into account the molecular diversity of the human cytome, will improve the predictive value of drug discovery.

Automated Interpretation of Protein Subcellular Location Patterns

Proteomics is a major current focus of biomedical research, and location proteomics is the important branch of proteomics that systematically studies the subcellular distributions for all proteins expressed in a given cell type. Fluorescence microscopy of labeled proteins is currently the main methodology to obtain location information. Traditionally, microscope images are analyzed by visual inspection, which suffers from inefficiency and inconsistency. Automated and objective interpretation approaches are therefore needed for location proteomics. In this article, we briefly review recent advances in automated imaging interpretation tools, including supervised classification (which assigns location pattern labels to previously unseen images), unsupervised clustering (which groups proteins based on the similarity among their subcellular distributions), and additional statistical tools that can aid cell and molecular biologists who use microscopy in their work.

Quantitative imaging of protein interactions in the cell nucleus

Over the past decade, genetically encoded fluorescent proteins have become widely used as noninvasive markers in living cells. The development of fluorescent proteins, coupled with advances in digital imaging, has led to the rapid evolution of live-cell imaging methods. These approaches are being applied to address biological questions of the recruitment, co-localization, and interactions of specific proteins within particular subcellular compartments. In the wake of this rapid progress, however, come important issues associated with the acquisition and analysis of ever larger and more complex digital imaging data sets. Using protein localization in the mammalian cell nucleus as an example, we will review some recent developments in the application of quantitative imaging to analyze subcellular distribution and co-localization of proteins in populations of living cells. In this report, we review the principles of acquiring fluorescence resonance energy transfer (FRET) microscopy measurements to define the spatial relationships between proteins. We then discuss how fluorescence lifetime imaging microscopy (FLIM) provides a method that is independent of intensity-based measurements to detect localized protein interactions with spatial resolution. Finally, we consider potential problems associated with the expression of proteins fused to fluorescent proteins for FRET-based measurements from living cells.

The Open Microscopy Environment (OME) Data Model and XML file: open tools for informatics and quantitative analysis in biological imaging

The Open Microscopy Environment (OME) defines a data model and software implementation to serve as an informatics framework for imaging in biological microscopy experiments.

The Open Microscopy Environment (OME) defines a data model and a software implementation to serve as an informatics framework for imaging in biological microscopy experiments, including representation of acquisition parameters, annotations and image analysis results. OME is designed to support high-content cell-based screening as well as traditional image analysis applications. The OME Data Model, expressed in Extensible Markup Language (XML) and realized in a traditional database, is both extensible and self-describing, allowing it to meet emerging imaging and analysis needs.

Imaging molecular interactions in living cells

Hormones integrate the activities of their target cells through receptor-modulated cascades of protein interactions that ultimately lead to changes in cellular function. Understanding how the cell assembles these signaling protein complexes is critically important to unraveling disease processes, and to the design of therapeutic strategies. Recent advances in live-cell imaging technologies, combined with the use of genetically encoded fluorescent proteins, now allow the assembly of these signaling protein complexes to be tracked within the organized microenvironment of the living cell. Here, we review some of the recent developments in the application of imaging techniques to measure the dynamic behavior, colocalization, and spatial relationships between proteins in living cells. Where possible, we discuss the application of these different approaches in the context of hormone regulation of nuclear receptor localization, mobility, and interactions in different subcellular compartments. We discuss measurements that define the spatial relationships and dynamics between proteins in living cells including fluorescence colocalization, fluorescence recovery after photobleaching, fluorescence correlation spectroscopy, fluorescence resonance energy transfer microscopy, and fluorescence lifetime imaging microscopy. These live-cell imaging tools provide an important complement to biochemical and structural biology studies, extending the analysis of protein-protein interactions, protein conformational changes, and the behavior of signaling molecules to their natural environment within the intact cell.

Quantitative methods to analyze subnuclear protein organization in cell populations with varying degrees of protein expression

The control of gene transcription is dependent on DNA-binding and coregulatory proteins that assemble in distinct regions of the cell nucleus. We use multispectral wide-field microscopy of cells expressing transcriptional coregulators labeled with fluorescent proteins (FP) to study the subnuclear localization and function of these factors in living cells. In coexpression studies, the glucocorticoid receptor interacting protein (GRIP) coactivator protein and the silencing mediator of retinoid and thyroid (SMRT) corepressor protein form spherical subnuclear focal bodies that are spatially distinct, suggesting that specific protein interactions concentrate these divergent proteins in separate subnuclear regions. However, the variability of these subnuclear bodies between cells within the population makes analysis based on "representative images" difficult, if not impossible. To address this issue, we develop a protocol for unbiased selection of cells from the population, followed by the automated quantification of the subnuclear organization of the labeled proteins. Statistical methods identify a significant linear correlation between the FP-coregulator expression level and subnuclear focal body formation for both FP-GRIP and FP-SMRT. Importantly, we confirm that these changes in subnuclear organization could be statistically normalized for differences in coregulator expression level. This integrated quantitative image analysis method will allow the rigorous comparison of different experimental cell populations that express variable levels of FP fusion proteins.

Alternatives to binary fission in bacteria

Whereas most prokaryotes rely on binary fission for propagation, many species use alternative mechanisms, which include multiple offspring formation and budding, to reproduce. In some bacterial species, these eccentric reproductive strategies are essential for propagation, whereas in others the programmes are used conditionally. Although there are tantalizing images and morphological descriptions of these atypical developmental processes, none of these reproductive structures are characterized at the molecular genetic level. Now, with newly available analytical techniques, model systems to study these alternative reproductive programmes are being developed.

Imaging protein behavior inside the living cell

The genetically encoded fluorescent proteins (FPs) have transformed studies in cell biology by allowing the behavior of proteins to be tracked within the natural environment of the living cell. Progressively more complex imaging methods are being used to measure the mobility, co-localization and interactions of proteins labeled with the FPs. This review provides an overview of recent developments in live-cell imaging techniques to analyze the subcellular distribution and interactions of proteins in living cells.

Subcellular topography of neuronal Abeta peptide in APPxPS1 transgenic mice

In transgenic mice expressing human mutant beta-amyloid precursor protein (APP) and mutant presenilin-1 (PS1), Abeta antibodies labeled granules, about 1 microm in diameter, in the perikaryon of neurons clustered in the isocortex, hippocampus, amygdala, thalamus, and brainstem. The granules were present before the onset of Abeta deposits; their number increased up to 9 months and decreased in 15-month-old animals. They were immunostained by antibodies against Abeta 40, Abeta 42, and APP C-terminal region. In double immunofluorescence experiments, the intracellular Abeta co-localized with lysosome markers and less frequently with MG160, a Golgi marker. Abeta accumulation correlated with an increased volume of lysosomes and Golgi apparatus, while the volume of endoplasmic reticulum and early endosomes did not change. Some granules were immunolabeled with an antibody against flotillin-1, a raft marker. At electron microscopy, Abeta, APP-C terminal, cathepsin D, and flotillin-1 epitopes were found in the lumen of multivesicular bodies. This study shows that Abeta peptide and APP C-terminal region accumulate in multivesicular bodies containing lysosomal enzymes, while APP N-terminus is excluded from them. Multivesicular bodies could secondarily liberate their content in the extracellular space as suggested by the association of cathepsin D with Abeta peptide in the extracellular space.

From quantitative microscopy to automated image understanding

Quantitative microscopy has been extensively used in biomedical research and has provided significant insights into structure and dynamics at the cell and tissue level. The entire procedure of quantitative microscopy is comprised of specimen preparation, light absorption/reflection/emission from the specimen, microscope optical processing, optical/electrical conversion by a camera or detector, and computational processing of digitized images. Although many of the latest digital signal processing techniques have been successfully applied to compress, restore, and register digital microscope images, automated approaches for recognition and understanding of complex subcellular patterns in light microscope images have been far less widely used. We describe a systematic approach for interpreting protein subcellular distributions using various sets of subcellular location features (SLF), in combination with supervised classification and unsupervised clustering methods. These methods can handle complex patterns in digital microscope images, and the features can be applied for other purposes such as objectively choosing a representative image from a collection and performing statistical comparisons of image sets.

Focusing light on infection in four dimensions

The fusion of cell biology with microbiology has bred a new discipline, cellular microbiology, in which the primary aim is to understand host-pathogen interactions at a tissue, cellular and molecular level. In this context, we require techniques allowing us to probe infection in situ and extrapolate quantitative information on its spatiotemporal dynamics. To these ends, fluorescent light-based imaging techniques offer a powerful tool, and the state-of-the-art is defined by paradigms using so-called multidimensional (multi-D) imaging microscopy. Multi-D imaging aims to visualize and quantify biological events through time and space and, more specifically, refers to combinations of: three (3D, volume), four (4D, time) and five (5D, multiwavelength)-dimensional recordings. Successful multi-D imaging depends upon understanding the available technologies and their limitations. This is especially true in the field of microbiology where visualization of infectious/pathogenic activities inside living host systems presents particular technical challenges. Thus, as multi-D imaging rapidly becomes a common bench tool to the cellular microbiologist, this review provides the new user with some of the necessary technical insight required to get the best from these methods.

Initiation of intracellular offspring in Epulopiscium

Epulopiscium spp. are the largest heterotrophic bacteria yet described. A distinguishing feature of the Epulopiscium group is their viviparous production of multiple, internal offspring as a means of cellular reproduction. Based on their phylogenetic position, among low G + C Gram-positive endospore-forming bacteria, and the remarkable morphological similarity between developing endospores and Epulopiscium offspring, we hypothesized that intracellular offspring production in Epulopiscium evolved from endospore formation. These observations also raise the possibility that a cell with the capacity to form multiple intracellular offspring was the ancestor of all contemporary endospore-forming bacteria. In an effort to characterize mechanisms common to both processes, we describe the earliest stages of offspring formation in Epulopiscium. First, in anticipation of polar division, some of the mother cell DNA coalesces at the cell poles. FtsZ then localizes in a bipolar pattern and the cell divides. A portion of the pole-associated DNA is trapped within the small cells formed by division at both poles. As development progresses, more pole-associated DNA is apparently packaged into the offspring primordia. These results illustrate three mechanisms, the reorganization of cellular DNA, asymmetric division and DNA packaging, that are common to both endospore formation in Bacillus subtilis and the production of active, intracellular offspring in Epulopiscium. Unlike most endospore formers, Epulopiscium partitions only a small proportion of mother cell DNA into the developing offspring.

Diminished surface clustering and increased perinuclear accumulation of large conductance Ca2+-activated K+ channel in mouse myometrium with pregnancy

Large conductance Ca2+-activated K+ channels play a critical role in regulating myometrium contractility. Their current density, mRNA, and total protein are greatly diminished in myometrium of late pregnant rats versus nonpregnant animals. Opposite to rats, in mice, channel mRNA and total protein increase in late pregnancy, but current density decreases as in rats. Here, we investigated the mechanism of these differences. Real time PCR and Western blots demonstrate that, in late pregnancy, channel transcript quantities and total protein were diminished in rats but up-regulated in mice. High resolution confocal microscopy of single myocytes showed that, in nonpregnant mice, channels were expressed in clusters at the surface membrane. In late pregnancy, although there was an overall increase in channel protein, its majority was accumulated in perinuclear organelles, and channel clustering practically disappeared from the surface membrane. This contrasts with rat myometrium, where there is a reduction of channel transcripts and overall protein levels including the surface membrane. We conclude that large conductance Ca2+-activated K+ channel surface expression is reduced in both rat and mouse late pregnant myometrium. However, in rats, the main mechanism for the reduced channel expression at the cell surface is a diminished transcription, whereas in mice, it is an altered traffic to the surface.

Informatics and quantitative analysis in biological imaging

Biological imaging is now a quantitative technique for probing cellular structure and dynamics and is increasingly used for cell-based screens. However, the bioinformatics tools required for hypothesis-driven analysis of digital images are still immature. We are developing the Open Microscopy Environment (OME) as an informatics solution for the storage and analysis of optical microscope image data. OME aims to automate image analysis, modeling, and mining of large sets of images and specifies a flexible data model, a relational database, and an XML-encoded file standard that is usable by potentially any software tool. With this design, OME provides a first step toward biological image informatics.

Live cell imaging using wide-field microscopy and deconvolution

The use of fluorescence imaging methods, most recently based on fluorescent protein technology, and the availability of high quality fluorescence imaging systems have driven a revolution in cell and molecular biology. Live cell imaging, especially using fluorescence, is now used in a wide variety of assays in academic and commercial laboratories. The use of this technology requires particular attention to be paid to cell engineering, the design of the image acquisition system, the imaging protocol, and subsequent processing and analytic methods. In this review, we discuss each of these steps, highlighting practical techniques developed by us and others.