Improved Visualization of Cell Nuclei in Unstained Cultured Cells

Nuclear morphology is useful in tissue culture studies in determining the presence and grade of transformed cells as well as in determining the heterogeneity of the cell population (Grogan el al. 1981, Hustin 1976, Siracky et al. 1978, Siracky 1979). The ratio of long and short nuclear axes provides a useful numerical expression of nuclear shape (Hustin 1976). Clear visualization of nuclei is critical for making the necessary measurements.     

应用小波变换检测细胞显微荧光图像中的囊泡

文章提出了一种用小波变换来检测生物荧光图像中囊泡的方法。作者用à trous小波对图像进行小波变换,然后求出每层系数的中值绝对偏差σ,并用t=kσ/0.67作为阈值对每层系数进行门限滤波,然后通过提取小波变换系数来重构图像。通过设计实验与常用的“rolling ball”算法对比,发现小波变换算法在低信噪比的情况下,具有更好的灵敏度;对于形状大小不同的信号,具有更好的稳定性;而且对于信号的细节信息具有更好的保真性。     

PombeX: Robust Cell Segmentation for Fission Yeast Transillumination Images

Schizosaccharomyces pombe shares many genes and proteins with humans and is a good model for chromosome behavior and DNA dynamics, which can be analyzed by visualizing the behavior of fluorescently tagged proteins in vivo. Performing a genome-wide screen for changes in such proteins requires developing methods that automate analysis of a large amount of images, the first step of which requires robust segmentation of the cell. We developed a segmentation system, PombeX, that can segment cells from transmitted illumination images with focus gradient and varying contrast. Corrections for focus gradient are applied to the image to aid in accurate detection of cell membrane and cytoplasm pixels, which is used to generate initial contours for cells. Gradient vector flow snake evolution is used to obtain the final cell contours. Finally, a machine learning-based validation of cell contours removes most incorrect or spurious contours. Quantitative evaluations show overall good segmentation performance on a large set of images, regardless of differences in image quality, lighting condition, focus condition and phenotypic profile. Comparisons with recent related methods for yeast cells show that PombeX outperforms current methods, both in terms of segmentation accuracy and computational speed.     

The Problem of Nucleolar Number in Cell Nuclei and in Sections of Cell Nuclei

In this paper the mean number N of nucleoli of cell nuclei and the relative frequency PN of cell nuclei with N nucleoli are investigated. To solve the first problem, the stereological model of convex shaped nuclei and nucleoli and the assumption of randomly-isotropically distributed objects in space are used. The model is developed for non-vanishing thickness T of tissue sections. The relationship between the unknown number N of nucleoli in cell nuclei and the mean number n of nucleoli in nuclear sections determined by counting is N = n (D+T)/(d + T). Here D and d are the mean values of caliper diameter for nuclei and for nucleoli, resp. The second problem is illustrated by means of some biomedical examples: The relative frequency PN of cell nuclei with N nucleoli can be approximated by a generalized Poisson distribution in all investigated cases. Therefore the mean nucleolar number N is the essential parameter to describe the frequencies of cell nuclei with different numbers of nucleoli.     

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.     

Birefringence and Paraffinophilia of Cell Nuclei

Birefringence of cell nuclei was present in most tissues but seen exclusively in paraffin sections. Only after staining with an acridinc derivative (rivanol) was it found in smears and frozen sections. Although retention of paraffin in the nucleus contributes, for the most part to its anisotropy, present evidence supports the hypothesis that the chemical nature and the physical state of nuclear material, especially of the DNA, plays the important role as a substrate, which selectively binds of paraffin molecules. This evidence is based mainly on the blocking effect on birefringence which occurs when small pieces of tissues are treated in toto, before paraffin embedding, with DNA-extracting procedures and nuclear stainings. Moreover, the variability in degree and extent of birefringence noted in different tissues corroborates this view. Factors in the preparatory procedure, i.e, deparaffinization, hydration and dehydration, were found to affect markedly the binding of paraffin to nuclear substance. Nevertheless, if paraffin affinity for nuclei is not considered, it may introduce inaccuracies into methods designed to determine the nuclear mass quantitatively, after staining.     

Segmentation of Fluorescence Microscopy Images for Quantitative Analysis of Cell Nuclear Architecture

Considerable advances in microscopy, biophysics, and cell biology have provided a wealth of imaging data describing the functional organization of the cell nucleus. Until recently, cell nuclear architecture has largely been assessed by subjective visual inspection of fluorescently labeled components imaged by the optical microscope. This approach is inadequate to fully quantify spatial associations, especially when the patterns are indistinct, irregular, or highly punctate. Accurate image processing techniques as well as statistical and computational tools are thus necessary to interpret this data if meaningful spatial-function relationships are to be established. Here, we have developed a thresholding algorithm, stable count thresholding (SCT), to segment nuclear compartments in confocal laser scanning microscopy image stacks to facilitate objective and quantitative analysis of the three-dimensional organization of these objects using formal statistical methods. We validate the efficacy and performance of the SCT algorithm using real images of immunofluorescently stained nuclear compartments and fluorescent beads as well as simulated images. In all three cases, the SCT algorithm delivers a segmentation that is far better than standard thresholding methods, and more importantly, is comparable to manual thresholding results. By applying the SCT algorithm and statistical analysis, we quantify the spatial configuration of promyelocytic leukemia nuclear bodies with respect to irregular-shaped SC35 domains. We show that the compartments are closer than expected under a null model for their spatial point distribution, and furthermore that their spatial association varies according to cell state. The methods reported are general and can readily be applied to quantify the spatial interactions of other nuclear compartments.     

A Novel Dictionary Based Computer Vision Method for the Detection of Cell Nuclei

Cell nuclei detection in fluorescent microscopic images is an important and time consuming task in a wide range of biological applications. Blur, clutter, bleed through and partial occlusion of nuclei make individual nuclei detection a challenging task for automated image analysis. This paper proposes a novel and robust detection method based on the active contour framework. Improvement over conventional approaches is achieved by exploiting prior knowledge of the nucleus shape in order to better detect individual nuclei. This prior knowledge is defined using a dictionary based approach which can be formulated as the optimization of a convex energy function. The proposed method shows accurate detection results for dense clusters of nuclei, for example, an F-measure (a measure for detection accuracy) of 0.96 for the detection of cell nuclei in peripheral blood mononuclear cells, compared to an F-measure of 0.90 achieved by state-of-the-art nuclei detection methods.     

Spatially Resolved Quantification of Chromatin Condensation through Differential Local Rheology in Cell Nuclei Fluorescence Lifetime Imaging

The linear sequence of DNA encodes access to the complete set of proteins that carry out cellular functions. Yet, much of the functionality appropriate for each cell is nested within layers of dynamic regulation and organization, including a hierarchy of chromatin structural states and spatial arrangement within the nucleus. There remain limitations in our understanding of gene expression within the context of nuclear organization from an inability to characterize hierarchical chromatin organization in situ. Here we demonstrate the use of fluorescence lifetime imaging microscopy (FLIM) to quantify and spatially resolve chromatin condensation state using cell-permeable, DNA-binding dyes (Hoechst 33342 and PicoGreen). Through in vitro and in situ experiments we demonstrate the sensitivity of fluorescence lifetime to condensation state through the mechanical effects that accompany the structural changes and are reflected through altered viscosity. The establishment of FLIM for resolving and quantifying chromatin condensation state opens the door for single-measurement mechanical studies of the nucleus and for characterizing the role of genome structure and organization in nuclear processes that accompany physiological and pathological changes.     

Magnesium and Calcium in Isolated Cell Nuclei

The calcium and magnesium contents of thymus nuclei have been determined and the nuclear sites of attachment of these two elements have been studied. The nuclei used for these purposes were isolated in non-aqueous media and in sucrose solutions. Non-aqueous nuclei contain 0.024 per cent calcium and 0.115 per cent magnesium. Calcium and magnesium are held at different sites. The greater part of the magnesium is bound to DNA, probably to its phosphate groups. Evidence is presented that the magnesium atoms combined with the phosphate groups of DNA are also attached to mononucleotides. There is reason to believe that those DNA-phosphate groups to which magnesium is bound, less than 1/10th of the total, are metabolically active, while those to which histones are attached seem to be inactive.     

Improved Methods for Reprogramming Human Dermal Fibroblasts Using Fluorescence Activated Cell Sorting

Current methods to derive induced pluripotent stem cell (iPSC) lines from human dermal fibroblasts by viral infection rely on expensive and lengthy protocols. One major factor contributing to the time required to derive lines is the ability of researchers to identify fully reprogrammed unique candidate clones from a mixed cell population containing transformed or partially reprogrammed cells and fibroblasts at an early time point post infection. Failure to select high quality colonies early in the derivation process results in cell lines that require increased maintenance and unreliable experimental outcomes. Here, we describe an improved method for the derivation of iPSC lines using fluorescence activated cell sorting (FACS) to isolate single cells expressing the cell surface marker signature CD13^NEGSSEA4^POSTra-1-60^POS on day 7–10 after infection. This technique prospectively isolates fully reprogrammed iPSCs, and depletes both parental and “contaminating” partially reprogrammed fibroblasts, thereby substantially reducing the time and reagents required to generate iPSC lines without the use of defined small molecule cocktails. FACS derived iPSC lines express common markers of pluripotency, and possess spontaneous differentiation potential in vitro and in vivo. To demonstrate the suitability of FACS for high-throughput iPSC generation, we derived 228 individual iPSC lines using either integrating (retroviral) or non- integrating (Sendai virus) reprogramming vectors and performed extensive characterization on a subset of those lines. The iPSC lines used in this study were derived from 76 unique samples from a variety of tissue sources, including fresh or frozen fibroblasts generated from biopsies harvested from healthy or disease patients.     

Semi-Automated Reconstruction of Neural Processes from Large Numbers of Fluorescence Images

We introduce a method for large scale reconstruction of complex bundles of neural processes from fluorescent image stacks. We imaged yellow fluorescent protein labeled axons that innervated a whole muscle, as well as dendrites in cerebral cortex, in transgenic mice, at the diffraction limit with a confocal microscope. Each image stack was digitally re-sampled along an orientation such that the majority of axons appeared in cross-section. A region growing algorithm was implemented in the open-source Reconstruct software and applied to the semi-automatic tracing of individual axons in three dimensions. The progression of region growing is constrained by user-specified criteria based on pixel values and object sizes, and the user has full control over the segmentation process. A full montage of reconstructed axons was assembled from the ∼200 individually reconstructed stacks. Average reconstruction speed is ∼0.5 mm per hour. We found an error rate in the automatic tracing mode of ∼1 error per 250 um of axonal length. We demonstrated the capacity of the program by reconstructing the connectome of motor axons in a small mouse muscle.     

基于多小波的胃癌病理细胞图像边缘检测与分析

对胃癌细胞图像的多尺度小波变换边缘检测进行了研究,为医生运用现代信息理论的方法进行相关疾病诊断提供了一种新的思路和途径。提出了多尺度小波边缘检测的新方法,归纳了改善小波边缘检测效果的一些策略。实验结果表明,对于具有复杂纹理的医学病理细胞图像,采用传统的边缘检测方法会产生伪边缘和方向性误差,它影响了图像边缘检测的可信度;而运用小波变换的时频尺度特性和对奇异变化的优良检测性能,可得到无噪声污染的图像实际边缘。     

Reactivation and Dedifferentiation of Differentiated Murine Erythroleukemic Cell Nuclei

A murine erythroleukemic cell line, 745 A4-TG, deficient in hypoxanthine-guanine-phosphoribosyl transferase, can be induced with 3 mM hexamethylene bisacetamide to yield at least 50% of cells undergoing irreversible erythroid differentiation and finally losing capacity for cell divisions. The effects of such induced differentiation of 745 A4-TG on its ability to form viable and proliferating hybrids when fused with 3T3 1T22 fibroblasts were investigated. We found that when the induced 745 A4-TG cells were used, more continuously proliferating hybrids were obtained than could be accounted for by the residual uninduced cells which remained in these induced preparations. This suggests that some of the induced 745 A4-TG cells, when fused with 3T3 1T22 reverted from the induced phenotype of a limited capacity for cell proliferation to an uninduced state of continuous proliferation. This observation was further confirmed with the use of fully differentiated 745 A4-TG cells, which were obtained after selection with a bromodeoxyuridine suicide treatment to eliminate the uninduced and the partially differentiated cells in the preparations. When these selected, fully differentiated cells, as characterized by their lack of proliferation capacity and thymidine kinase activity, were fused with 3T3 1T22 (also deficient in thymidine kinase), it was found that not only were viable hybrid colonies obtained in a selection medium, which precluded the proliferation of either parental cells, but these hybrids continued to proliferate for more than two months in selection medium. These data thus confirmed that some fully differentiated erythroleukemic nucleus components in the hybrids were reactivated to regain capacity for cell proliferation and to dedifferentiate to synthesize thymidine kinase for survival in the selection medium. The lack of hemoglobin synthesis by these hybrids also indicates dedifferention of these murine erythroleukemic components in the hybrids.     

Rapid Analysis and Exploration of Fluorescence Microscopy Images

Despite rapid advances in high-throughput microscopy, quantitative image-based assays still pose significant challenges. While a variety of specialized image analysis tools are available, most traditional image-analysis-based workflows have steep learning curves (for fine tuning of analysis parameters) and result in long turnaround times between imaging and analysis. In particular, cell segmentation, the process of identifying individual cells in an image, is a major bottleneck in this regard.Here we present an alternate, cell-segmentation-free workflow based on PhenoRipper, an open-source software platform designed for the rapid analysis and exploration of microscopy images. The pipeline presented here is optimized for immunofluorescence microscopy images of cell cultures and requires minimal user intervention. Within half an hour, PhenoRipper can analyze data from a typical 96-well experiment and generate image profiles. Users can then visually explore their data, perform quality control on their experiment, ensure response to perturbations and check reproducibility of replicates. This facilitates a rapid feedback cycle between analysis and experiment, which is crucial during assay optimization. This protocol is useful not just as a first pass analysis for quality control, but also may be used as an end-to-end solution, especially for screening. The workflow described here scales to large data sets such as those generated by high-throughput screens, and has been shown to group experimental conditions by phenotype accurately over a wide range of biological systems. The PhenoBrowser interface provides an intuitive framework to explore the phenotypic space and relate image properties to biological annotations. Taken together, the protocol described here will lower the barriers to adopting quantitative analysis of image based screens.     

Bright Field Microscopy as an Alternative to Whole Cell Fluorescence in Automated Analysis of Macrophage Images

Background

Fluorescence microscopy is the standard tool for detection and analysis of cellular phenomena. This technique, however, has a number of drawbacks such as the limited number of available fluorescent channels in microscopes, overlapping excitation and emission spectra of the stains, and phototoxicity.

Methodology

We here present and validate a method to automatically detect cell population outlines directly from bright field images. By imaging samples with several focus levels forming a bright field -stack, and by measuring the intensity variations of this stack over the -dimension, we construct a new two dimensional projection image of increased contrast. With additional information for locations of each cell, such as stained nuclei, this bright field projection image can be used instead of whole cell fluorescence to locate borders of individual cells, separating touching cells, and enabling single cell analysis. Using the popular CellProfiler freeware cell image analysis software mainly targeted for fluorescence microscopy, we validate our method by automatically segmenting low contrast and rather complex shaped murine macrophage cells.

Significance

The proposed approach frees up a fluorescence channel, which can be used for subcellular studies. It also facilitates cell shape measurement in experiments where whole cell fluorescent staining is either not available, or is dependent on a particular experimental condition. We show that whole cell area detection results using our projected bright field images match closely to the standard approach where cell areas are localized using fluorescence, and conclude that the high contrast bright field projection image can directly replace one fluorescent channel in whole cell quantification. Matlab code for calculating the projections can be downloaded from the supplementary site: http://sites.google.com/site/brightfieldorstaining     

An Analytical Tool that Quantifies Cellular Morphology Changes from Three-dimensional Fluorescence Images

The most common software analysis tools available for measuring fluorescence images are for two-dimensional (2D) data that rely on manual settings for inclusion and exclusion of data points, and computer-aided pattern recognition to support the interpretation and findings of the analysis. It has become increasingly important to be able to measure fluorescence images constructed from three-dimensional (3D) datasets in order to be able to capture the complexity of cellular dynamics and understand the basis of cellular plasticity within biological systems. Sophisticated microscopy instruments have permitted the visualization of 3D fluorescence images through the acquisition of multispectral fluorescence images and powerful analytical software that reconstructs the images from confocal stacks that then provide a 3D representation of the collected 2D images. Advanced design-based stereology methods have progressed from the approximation and assumptions of the original model-based stereology¹ even in complex tissue sections². Despite these scientific advances in microscopy, a need remains for an automated analytic method that fully exploits the intrinsic 3D data to allow for the analysis and quantification of the complex changes in cell morphology, protein localization and receptor trafficking. Current techniques available to quantify fluorescence images include Meta-Morph (Molecular Devices, Sunnyvale, CA) and Image J (NIH) which provide manual analysis. Imaris (Andor Technology, Belfast, Northern Ireland) software provides the feature MeasurementPro, which allows the manual creation of measurement points that can be placed in a volume image or drawn on a series of 2D slices to create a 3D object. This method is useful for single-click point measurements to measure a line distance between two objects or to create a polygon that encloses a region of interest, but it is difficult to apply to complex cellular network structures. Filament Tracer (Andor) allows automatic detection of the 3D neuronal filament-like however, this module has been developed to measure defined structures such as neurons, which are comprised of dendrites, axons and spines (tree-like structure). This module has been ingeniously utilized to make morphological measurements to non-neuronal cells³, however, the output data provide information of an extended cellular network by using a software that depends on a defined cell shape rather than being an amorphous-shaped cellular model. To overcome the issue of analyzing amorphous-shaped cells and making the software more suitable to a biological application, Imaris developed Imaris Cell. This was a scientific project with the Eidgenössische Technische Hochschule, which has been developed to calculate the relationship between cells and organelles. While the software enables the detection of biological constraints, by forcing one nucleus per cell and using cell membranes to segment cells, it cannot be utilized to analyze fluorescence data that are not continuous because ideally it builds cell surface without void spaces. To our knowledge, at present no user-modifiable automated approach that provides morphometric information from 3D fluorescence images has been developed that achieves cellular spatial information of an undefined shape (Figure 1). We have developed an analytical platform using the Imaris core software module and Imaris XT interfaced to MATLAB (Mat Works, Inc.). These tools allow the 3D measurement of cells without a pre-defined shape and with inconsistent fluorescence network components. Furthermore, this method will allow researchers who have extended expertise in biological systems, but not familiarity to computer applications, to perform quantification of morphological changes in cell dynamics.