Computational imaging in cell biology

An automatic method for identifying appropriate gradient magnitude for 3D boundary detection of confocal image stacks

Gradients play an important role in 2D image processing. Many edge detection algorithms are gradient-based. We are interested in 3D boundary detection which can be considered as an extension of 2D edge detection in 3D space. In this paper, an algorithm to automatically and quantitatively measure the suitability of gradient magnitudes in detection of 3D boundary points of confocal image stacks is presented. A Measurement Function is defined to evaluate the suitability of each gradient magnitude chosen to be the threshold for 3D boundary detection. The application of Gauss's Divergence Theorem provides a solution to calculate the Measurement Function numerically. The gradient magnitude at which the maximum of the Measurement Function is achieved can be utilized as the most appropriate threshold for gradient-based boundary detection and other operations like volume visualization.

New insights into extracellular matrix assembly and reorganization from dynamic imaging of extracellular matrix proteins in living osteoblasts

The extracellular matrix (ECM) has been traditionally viewed as a static scaffold that supports cells and tissues. However, recent dynamic imaging studies suggest that ECM components are highly elastic and undergo continual movement and deformation. Latent transforming growth factor beta (TGFbeta) binding protein-1 (LTBP1) is an ECM glycoprotein that binds latent TGFbeta and regulates its availability and activity. LTBP1 initially co-distributes with fibronectin in the extracellular matrix of osteoblasts, and depends on fibronectin for its assembly. To gain further insights into the mechanisms of assembly of LTBP1 and its spatial and temporal interactions with fibronectin, we have performed dual fluorescence time-lapse imaging of these two proteins in living osteoblasts using fluorescent probes. Time-lapse movies showed surprisingly large fibril displacements associated with cellular movement as well as occasional breaking of LTBP1 or fibronectin-containing fibrils. Individual fibrils stretched to as much as 3.5 times or contracted to as much as one fourth of their original length. Motile cells appeared to actively mediate extracellular matrix assembly by adding 'globules' or 'packets' of matrix material onto existing fibrils. They also actively reorganized the extracellular matrix by shunting matrix material from one location to another and exchanging fibrillar material between fibrils. This cell-mediated matrix reorganization was primarily associated with the assembly and remodeling of the initial (early) matrix, whereas mature, established ECM was more stable. Displacement vector mapping showed that different matrix fibrillar networks within the same cultures can show different dynamic motion in response to cell movement and showed that the motion of fibrils was correlated with cell motion. These data suggest novel cell-mediated mechanisms for assembly and reorganization of the extracellular matrix and highlight a role for cell motility in the assembly process.

Automated local bright feature image analysis of nuclear protein distribution identifies changes in tissue phenotype

The organization of nuclear proteins is linked to cell and tissue phenotypes. When cells arrest proliferation, undergo apoptosis, or differentiate, distribution of nuclear proteins changes. Conversely, forced alteration of the distribution of nuclear proteins modifies cell phenotype. Immunostaining and fluorescence microscopy have been critical for such findings. However, there is increasing need for quantitative analysis of nuclear protein distribution to decipher epigenetic relationships between nuclear structure and cell phenotype and to unravel the mechanisms linking nuclear structure and function. We have developed imaging methods to quantify the distribution of fluorescently stained nuclear protein NuMA in different mammary phenotypes obtained using 3D cell culture. Automated image segmentation of DAPI-stained nuclei was generated to isolate thousands of nuclei from 3D confocal images. Prominent features of fluorescently stained NuMA were detected by using a previously undescribed local bright feature analysis technique, and their normalized spatial density was calculated as a function of the distance from the nuclear perimeter to its center. The results revealed marked changes in the distribution of the density of NuMA bright features when nonneoplastic cells underwent phenotypically normal acinar morphogenesis. Conversely, we did not detect any reorganization of NuMA during formation of tumor nodules by malignant cells. Importantly, the analysis also discriminated proliferating nonneoplastic from proliferating malignant cells, suggesting that these imaging methods are capable of identifying alterations linked not only to the proliferation status but also to the malignant character of cells. We believe that this quantitative analysis will have additional applications for classifying normal and pathological tissues.

Automated cell lineage tracing in Caenorhabditis elegans

The invariant cell lineage and cell fate of Caenorhabditis elegans provide a unique opportunity to decode the molecular mechanisms of animal development. To exploit this opportunity, we have developed a system for automated cell lineage tracing during C. elegans embryogenesis, based on 3D, time-lapse imaging and automated image analysis. Using ubiquitously expressed histone-GFP fusion protein to label cells/nuclei and a confocal microscope, the imaging protocol captures embryogenesis at high spatial (31 planes at 1 microm apart) and temporal (every minute) resolution without apparent effects on development. A set of image analysis algorithms then automatically recognizes cells at each time point, tracks cell movements, divisions and deaths over time and assigns cell identities based on the canonical naming scheme. Starting from the four-cell stage (or earlier), our software, named starrynite, can trace the lineage up to the 350-cell stage in 25 min on a desktop computer. The few errors of automated lineaging can then be corrected in a few hours with a graphic interface that allows easy navigation of the images and the reported lineage tree. The system can be used to characterize lineage phenotypes of genes and/or extended to determine gene expression patterns in a living embryo at the single-cell level. We envision that this automation will make it practical to systematically decipher the developmental genes and pathways encoded in the genome of C. elegans.

Dynamics of Assembly and Reorganization of Extracellular Matrix Proteins

This chapter will review advances in our understanding of the dynamics of assembly and reorganization of extracellular matrix (ECM) proteins and will highlight the role of fibronectin as a key orchestrator for the assembly of multiple ECM proteins. The dynamic rather than static nature of the ECM will be emphasized by reviewing time-lapse imaging studies in living cell and embryo systems, with a particular focus on fibronectin and members of the fibrillin superfamily. These studies have provided new insights into the assembly and reorganization of ECM fibrillar networks, suggesting that fibril assembly is a hierarchical process, with increasingly larger fibrillar structures formed by the progressive aggregation of smaller units. These studies have also revealed that motile cells appear to be actively involved in the assembly and reorganization of ECM fibrillar networks by shunting fibrillar material from one location to another, adding fibrillar material to the ends of growing fibrils, and exchanging material between fibrils. A common theme emerging from these studies is that cell- and tissue-generated mechanical forces are critical in the assembly and remodeling of the ECM.

Subnuclear organelles: new insights into form and function

The cell nucleus is a complex and highly dynamic environment with many functionally specialized regions of substructure that form and maintain themselves in the absence of membranes. Relatively little is known about the basic physical properties of the nuclear interior or how domains within the nucleus are structurally and functionally organized and interrelated. Here, we summarize recent data that shed light on the structural and functional properties of three prominent subnuclear organelles--nucleoli, Cajal bodies (CBs) and speckles. We discuss how these findings impact our understanding of the guiding principles of nuclear organization and various types of human disease.

Comparison of intensity based similarity measures for matching genomic structures in microscopic images of living cells

This paper presents our comparative study of the application of intensity based similarity measures to the problem of matching genomic structures in microscopic images of living cells. As part of our ongoing research, we present here for the first time evidence from experiments and simulations that show the benefit of using an iterative matching algorithm guided by an intensity based similarity measure. Our experimental results are compared against a gold standard and suggest the measures that work best in the presence of fluorescent decay and other problems inherent to time-lapse microscopy. This makes our approach widely applicable in the study of the dynamics of living cells with time-lapse microscopic imaging.

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.

Cell microarrays and RNA interference chip away at gene function

The recent development of cell microarrays offers the potential to accelerate high-throughput functional genetic studies. The widespread use of RNA interference (RNAi) has prompted several groups to fabricate RNAi cell microarrays that make possible discrete, in-parallel transfection with thousands of RNAi reagents on a microarray slide. Though still a budding technology, RNAi cell microarrays promise to increase the efficiency, economy and ease of genome-wide RNAi screens in metazoan 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.

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.

Space as the final frontier in stochastic simulations of biological systems

Recent technological and theoretical advances are only now allowing the simulation of detailed kinetic models of biological systems that reflect the stochastic movement and reactivity of individual molecules within cellular compartments. The behavior of many systems could not be properly understood without this level of resolution, opening up new perspectives of using computer simulations to accelerate biological research. We review the modeling methodology applied to stochastic spatial models, also to the attention of non-expert potential users. Modeling choices, current limitations and perspectives of improvement of current general-purpose modeling/simulation platforms for biological systems are discussed.

4-D single particle tracking of synthetic and proteinaceous microspheres reveals preferential movement of nuclear particles along chromatin - poor tracks

Background

The dynamics of nuclear organization, nuclear bodies and RNPs in particular has been the focus of many studies. To understand their function, knowledge of their spatial nuclear position and temporal translocation is essential. Typically, such studies generate a wealth of data that require novel methods in image analysis and computational tools to quantitatively track particle movement on the background of moving cells and shape changing nuclei.

Results

We developed a novel 4-D image processing platform (TIKAL) for the work with laser scanning and wide field microscopes. TIKAL provides a registration software for correcting global movements and local deformations of cells as well as 2-D and 3-D tracking software. With this new tool, we studied the dynamics of two different types of nuclear particles, namely nuclear bodies made from GFP-NLS-vimentin and microinjected 0.1 μm – wide polystyrene beads, by live cell time-lapse microscopy combined with single particle tracking and mobility analysis. We now provide a tool for the automatic 3-D analysis of particle movement in parallel with the acquisition of chromatin density data.

Conclusions

Kinetic analysis revealed 4 modes of movement: confined obstructed, normal diffusion and directed motion. Particle tracking on the background of stained chromatin revealed that particle movement is directly related to local reorganization of chromatin. Further a direct comparison of particle movement in the nucleoplasm and the cytoplasm exhibited an entirely different kinetic behaviour of vimentin particles in both compartments.

The kinetics of nuclear particles were slightly affected by depletion of ATP and significantly disturbed by disruption of actin and microtubule networks. Moreover, the hydration state of the nucleus had a strong impact on the mobility of nuclear bodies since both normal diffusion and directed motion were entirely abolished when cells were challenged with 0.6 M sorbitol. This effect correlated with the compaction of chromatin. We conclude that alteration in chromatin density directly influences the mobility of protein assemblies within the nucleus.

Nuclear body movement is determined by chromatin accessibility and dynamics

Promyelocytic leukemia (PML) and Cajal bodies are mobile subnuclear organelles, which are involved in activities like RNA processing, transcriptional regulation, and antiviral defense. A key parameter in understanding their biological functions is their mobility. The diffusion properties of PML and Cajal bodies were compared with a biochemically inactive body formed by aggregates of murine Mx1 by using single-particle tracking methods. The artificial Mx1-yellow fluorescent protein body showed a very similar mobility compared with PML and Cajal bodies. The data are described quantitatively by a mechanism of nuclear body movement consisting of two components: diffusion of the body within a chromatin corral and its translocation resulting from chromatin diffusion. This finding suggests that the body mobility reflects the dynamics and accessibility of the chromatin environment, which might target bodies to specific nuclear subcompartments where they exert their biological function.

Computer-assisted image analysis protocol that quantitatively measures subnuclear protein organization in cell populations

Many nuclear proteins, including the nuclear receptor co-repressor (NCoR) protein are localized to specific regions of the cell nucleus, and this subnuclear positioning is preserved when NCoR is expressed in cells as a fusion to a fluorescent protein (FP). To determine how specific factors may influence the subnuclear organization of NCoR requires an unbiased approach to the selection of cells for image analysis. Here, we use the co-expression of the monomeric red FP (mRFP) to select cells that also express NCoR labeled with yellow FP (YFP). The transfected cells are selected for imaging based on the diffuse cellular mRFP signal without prior knowledge of the subnuclear organization of the co-expressed YFP-NCoR. The images acquired of the expressed FPs are then analyzed using an automated image analysis protocol that identifies regions of interest (ROIs) using a set of empirically determined rules. The relative expression levels of both fluorescent proteins are estimated, and YFP-NCoR subnuclear organization is quantified based on the mean focal body size and relative intensity. The selected ROIs are tagged with an identifier and annotated with the acquired data. This integrated image analysis protocol is an unbiased method for the precise and consistent measurement of thousands of ROIs from hundreds of individual cells in the population.