Journal of Histochemistry and Cytochemistry, Vol. 45, 1097-1108, Copyright © 1997 by The Histochemical Society, Inc.


ARTICLE

Chromatin Condensation in Erythropoiesis Resolved by Multipixel Spectral Imaging: Differentiation Versus Apoptosis

Chana Rothmanna, Amos M. Cohenb, and Zvi Malika
a Life Sciences Department, Bar Ilan University, Ramat-Gan, Israel
b Hematology Unit, Rabin Medical Center, Golda Campus, Petach Tiqua, Israel

Correspondence to: Zvi Malik, Life Sciences Dept., Bar Ilan University, Ramat-Gan 52900, Israel.


  Summary
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Summary
Introduction
Materials and Methods
Results
Discussion
Literature Cited

Chromatin condensation and nuclear organization of May-Grunwald-Giemsa (MGG)-stained normal erythropoietic bone marrow cells and apoptotic red cell precursors were resolved by spectral bio-imaging. Multipixel spectra were obtained from single cells displaying a range of wavelengths of both transmitted and absorbed light. Two groups of spectra, of low- and high-intensity transmitted light, were revealed in the nuclei of each cell. The absorbance spectra served for the reconstruction of "absorbance images" depicting the affinity of MGG stain for the chromatin of proerythroblasts and of basophilic, polychromatic, and orthochromatic normoblasts. The localization of different spectral components in the nuclei was resolved employing two mathematical methods, spectral similarity mapping and principal component analysis. Novel structures of high symmetry revealing windmill-like organization were detected in basophilic, polychromatic, and orthochromatic normoblast cells. Matching structures were detected in apoptotic normoblasts obtained from an agnogenic myeloid metaplasia patient. Apoptosis was associated with a gradual breakdown of the ordered arrays in the nucleus. We propose that DNA cleavage may lead to fragmentation of the symmetrical windmill-like superstructure of the basic nuclear domains. (J Histochem Cytochem 45:1097-1108, 1997)

Key Words: multipixel spectroscopy, spectral similarity mapping, absorbance image, eigen images, apoptosis imaging, erythropoiesis imaging


  Introduction
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Summary
Introduction
Materials and Methods
Results
Discussion
Literature Cited

Terminal erythroid differentiation and apoptosis share common processes of nuclear chromatin condensation and cell volume decrease. However, morphological and biochemical distinctions between these two processes have been described (Kelley et al. 1993 ). In terminal human erythroid differentiation, nuclear envelope preservation occurs simultaneously with chromatin condensation and hemoglobin synthesis. In apoptosis, the homogeneous nuclear condensation and fragmentation was shown to be accompanied by nuclear envelope loss, either at or before the stage of hemoglobin synthesis (Kelley et al. 1993 ).

Nuclear chromatin structure is modulated by histone-histone, histone-DNA interactions, histone modifications, and by the presence of non-histone proteins (Woodcock and Horowitz 1995 ). The accessibility of a specific DNA sequence is a consequence of the compaction state of the chromatin in which it is located. Therefore, the accessibility of a highly condensed chromatin is likely to be extremely restricted (Woodcock and Horowitz 1995 ). Hence, variability in chromatin organization in differentiating cells and in abnormal cells can be regarded as a reliable tool for cytology and pathological histology.

During maturation of the red cell precursors, the nucleus exhibits a series of qualitative morphological changes (Papayannopoulou and Abkowitz 1991 ). Nuclear maturation abnormalities in either proerythroblasts or normoblasts are observed in various conditions, such as vitamin B12 or folate deficiency, myelodysplastic syndrome, and effects of chemotherapy. Although there is presently no evidence for programmed cell death in normal erythropoiesis, the late orthochromatic erythroblast with its shrunken pyknotic nucleus morphologically resembles an apoptotic cell (Yuan et al. 1993 ).

Apoptosis is a process of active cell death associated with distinctive morphological and biological events such as nuclear condensation (pyknosis) and fragmentation (karyorrhexis), with internucleosomal cleavage of cellular DNA (Muta and Krantz 1993 ). Programmed cell death has been demonstrated for many tissues and cell lines as a selective process of physiological cell deletion. It plays a major role in the control of normal and abnormal processes. Apoptosis has been described in erythroid precursors in in vitro systems of cells derived from patients with severe ß-thalassemia and folate deficiency (Yuan et al. 1993 ).

The hematopoietic progenitor cells in folate-deficient individuals have nuclear irregularities including increased size, lobulation, and fragmentation. These abnormalities in the nuclei and the DNA imply the disruption of biochemical reactions that require folate co-enzymes and are in a pathway that lead to DNA synthesis (Koury and Home 1994 ). Koury and Home 1994 found that decreased thymidylate synthesis plays a role in erythroblast apoptosis in anemia of folate deficiency.

Biological applications of image analysis include the analysis of chromosomal structure, cell ploidity quantitative immunohistochemistry (Goto et al. 1992 ; Santeusanio et al. 1992 ). A limited amount of spectral information can be obtained by using charge-coupled detectors (cooled CCD; Princeton Instruments, Trenton, NJ), with or without narrow-pass filters for color separation, in light microscopy of chromophore binding or of environmental effects on the dye. By employing narrow-pass filters for imaging, the spectral information is limited to some narrow bands and an entire spectral range may not be obtained. Image analysis can be improved by the combination of accurate spectroscopy with imaging, adding point-by-point spectral information to the structural perception. The most common methods involve selected-region microspectroscopy of an entire cell or introduction of spot diaphragms to measure the spectrum from a small defined region of a cell.

Standard analysis of blood cells for the determination of differentiation and pathological conditions is based on staining with MGG or Romanowsky techniques, which employ the dyes azure B and eosin. Spectroscopic selected area microanalysis has been shown to enhance the data obtained from cells stained by standard methods. By a spectral subtraction technique, Galbraith et al. 1980 have shown that the differential coloration of various cell structures can be explained in terms of varying proportions of dye components. Friedrich et al. 1990 have shown that Romanowsky-Giemsa-stained cell nuclei have a sharp and intense absorption band at 552 nm, the so-called Romanowsky band, which is attributed to the dye complexes of the eosin chromophore. Other absorption bands were assigned to the DNA-bound azure B cations (Friedrich et al. 1990 ). The eosin anions are mainly bound by hydrophobic interaction to the azure B framework of the electrically neutral DNA-azure B complexes. The eosin absorption is red-shifted by the interaction of eosin with the azure B framework of the DNA-azure B-eosin complexes (Friedrich et al. 1990 ). By adopting computerized spectroscopic microanalyis of nuclear chromatin granularity, Spina et al. 1992 showed a significant distinction between benign and malignant breast cells. The principle of this approach was based on analysis of the abrupt transition from eurochromatic to heterochromatic foci of high-contrast gradient as a parameter for coarseness in smears stained by the MGG technique. In this technique, computer-assisted subtraction between two images obtained with lowpass filters retained only high-contrast gradient values on the digitized image. Therefore, the stained nucleus may preserve much more information on its fine structure than our bare eye can define by conventional light microscopy.

We have recently described new techniques of Fourier transform multipixel spectroscopy for light microscopy (Garini et al. 1996 ; Malik et al. 1996a , Malik et al. 1996b ; Simon-Blecher et al. 1996 ; Katz et al. 1997 ). Spectrally resolved multipixel image analysis combines spectral data with imaging for cell biology. Essentially, the demand from a spectral image is to present a three-dimensional array of data that combines precise spectral information with two-dimensional spatial correlation. The analysis of a spectral image creates a unique database that enables the extraction of features and the evaluation of quantities from multipoint spectral information that would be impossible to obtain otherwise. The interferogram is measured individually at each pixel in a CCD array (Morris et al. 1994 ). Fourier transformation thus yields a distinct spectrum at each pixel. Interferometric Fourier spectroscopy enjoys several important advantages in comparison to dispersion methods; it provides high optical accuracy, high and variable spectral resolution, wide spectral range, and mechanical/thermal stability (Chamberlin 1978 ; Vane et al. 1988 ).

To determine chromatin organization in erythroid cells stained with MGG, we employed a novel technique of spectrally resolved image analysis. Morphological patterns of chromatin organization during normal erythroid differentiation and apoptosis were determined by mathematical methods of spectral similarity mapping and principal component analysis.


  Materials and Methods
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Summary
Introduction
Materials and Methods
Results
Discussion
Literature Cited

Fourier Transform Multipixel Spectrometry System for Microscopy
Spectral imaging was performed using the SpectraCube SD-200 (Applied Spectral Imaging; Migdal HaEmek, Israel). The SpectraCube system consists of an interferometer situated in the parallel beam between an objective lens (infinity corrected) and a lens equivalent to an eyepiece, whose purpose is to form an image on a CCD camera. The light beam passing through the specimen is split in the interferometer in opposite directions, and is united again at the exit with an optical path difference (OPD) that is a function of the angle between the incoming beam and the interferometer itself. The OPD arises because for non-zero angles the two beams undergo different optical paths in the beamsplitter. The inherent mechanical stability of this interferometer allows the Fourier technique to be successfully applied to the visible spectral region. The measurement is done by recording successive CCD frames in synchronization with the steps of the motor used to rotate the collimated beam, so that the instantaneous OPD is known for every pixel in every recorded frame and can be used in the FFT calculation (Malik et al. 1996a ). During a measurement (20 sec), each pixel of the CCD (512 x 512) is collecting the interferogram, which is then Fourier transformed to give the spectrum.

Briefly, in spectral imaging, each pixel is actually one of several tens of thousands of microspectrometers, acting simultaneously and independently. As a result, spectral imaging acquires a so-called cube whose appellate signifies the two spatial dimensions of a flat sample (x and y), and the third wavelength dimension. The calculated pixel size in a spectral image is 0.04 µm2. The spectral resolution (FWHM, full width at half maximum) is 5 nm at 400 nm (12 nm at 600 nm) and the spectral range (more than 5% response) is 400-1000 nm (Garini et al. 1996 ).

Optical Density and Absorbance Images
The estimation of chromatin optical density was obtained by applying the Beer-Lambert law for absorbance:

where I0 is the illuminating incident light in the microscope, It is the transmitted light passing through the specimen at a specific site, {epsilon} is the absorption coefficient of macromolecules, c their concentration, and l sample thickness. The {epsilon}cl values cannot be determined for a cellular compartment and therefore they were replaced by an arbitrary constant k, standing for . The equation defines optical density values rather than absolute absorbance. For these calculations, the incident light was defined as a pixel outside a cell. Absorbance spectra served for construction of absorbance images.

Similarity Mapping Analysis
To segregate different regions in the sample, we employed the spectral similarity mapping mathematical function, which calculates the differences between area integrals of one chosen spectrum with respect to all the other spectra composing an image. The comparison algorithm used in this work for similarity mapping is defined by the following function:

where Ix,y, is the spectrum of the pixel of coordinates x and y of the image, as a function of {lambda}. The integral stands for an interval over a predetermined spectral range {lambda}1 - {lambda}2 and I0 is the reference spectrum (average of 9 pixels) chosen in a region where the feature of interest is present.

The reconstructed similarity map image composed of bright and gray pixels reveals the degree of similarity between the spectra. The brighter the pixel, the more the two spectra are alike.

Principal Component Analysis
Principal component analysis (also referred to as eigenvector) uses linear transformation of multiband data to translate and rotate data into a new coordinate system that maximizes the variance. This technique is useful for enhancing the information content, segregating noise components, and for reducing the dimensionality of data sets. The original data are arranged in a population of x vectors. The components of each vector are the intensity values of a certain pixel at the different spectral slices. The covariance matrix of the vector population is defined as:

where T indicates vector transposition and mx is the mean vector of the population. Principal component analysis can be described in the following equation:

where A is the matrix whose rows are formed from the eigenvectors of Cx ordered so that the first row of A is the eigenvector corresponding to the largest eigenvalue and the last row is the eigenvector corresponding to the smallest eigenvalue (Gonzalez and Woods 1993 ).

May-Grunwald Staining of Bone Marrow Specimens
Bone marrow aspiration biopsy specimens were obtained from patients with non-hematologic disorders and peripheral blood from a patient with agnogenic myeloid metaplasia (AMM) with a leukoerythroblastic blood picture (Ward and Block 1971 ; Reilly 1994 ). None of the patients received chemotherapy for at least 3 months before the samples were obtained. Staining was performed according to the MGG method.

Flow Cytometry
Apoptotic cells were assayed for DNA content using the propidium iodide (PI) staining method and subsequent flow cytometry analysis. Briefly, the cells (usually 2 x 106) were washed twice with PBS, centrifuged, and fixed in 70% ethanol. The fixed cells were pelleted, resuspended in PBS, and incubated at 37C for 30 min with 100 µg/ml RNAse A and 5 µg/ml PI [prepared in PBS at 100 µg/ml and kept in the dark at room temperature (RT)]. Analyses of the cells for cell-cycle status were performed using a Becton-Dickinson FACSort. For each sample, 10,000 cells were analyzed with gating to exclude doublets. The data were collected and deconvoluted by a cell-fit program.

Electron Microscopy
For transmission electron microscopy, the cells were fixed with 2.0% paraformaldehyde and 2.5% glutaraldehyde for 1 hr at RT. The cells were postfixed with 1% osmium tetroxide for an additional hour at 4C, dehydrated in alcohol, and embedded in Epon. Thin sections were stained with uranyl acetate and lead citrate and photographed using a JEOL 1200EX transmission electron microscope.

For scanning electron microscopy, the fixed cells were washed twice in Ca+2 + Mg+2-free Dulbecco's phosphate-buffered saline and dehydrated by immersion in a gradient of ethanol solutions. Then ethanol was exchanged with Freon 113 and the cells were critical point-dried. Specimens were coated with gold and micrographs were taken with a JEOL JSM 840 scanning electron microscope.


  Results
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Materials and Methods
Results
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Spectral Analysis
Figure 1A-D show MGG-stained erythropoietic progenitor cells and their corresponding multipixel transmitted light spectra of the chromatin. Each spectrum in Figure 1E-H is the average of a sample of 10 pixels arbitrarily chosen from two domains, one with low-intensity light transmittance (LIT) and the other with high-intensity light transmittance (HIT), out of 4 x 104 pixel spectra composing multiple cellular sites of the single cell in Figure 1A-D. Therefore, the spectrally resolved image of an erythropoietic cell is a three-dimensional set of data: f (x,y,{lambda}) for each pixel at plane x,y; the third dimension is its wavelength {lambda}. The transmittance spectra of progenitor erythroid cell nuclei depict a similar pattern: a low-intensity light transmittance region in the range of 550-750 nm in comparison to the high-intensity light transmittance region. Therefore, the spectra of corresponding cells in Figure 1A-D may show some specific changes related to the differentiation and cytological transformation, as shown in Figure 1E-H.




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Figure 1. Multipixel spectra obtained from MGG stained bone marrow erythropoietic cells. (A-D) Proerythroblast, basophilic, polychromatic, and orthochromatic normoblasts, respectively; A-D are true color images presented on a gray scale. Bar = 5 µm. (E-H) Transmitted light spectra of the same cells; the two sets of 10 arbitrarily chosen pixels were each obtained from the different regions of the nucleus (±SE). HIT, high-intensity light transmittance; LIT, low-intensity light transmittance. (I-L) Optical density spectra of the same cells calculated as described in Materials and Methods. The two sets of 10 different pixels were each obtained from the different regions of the nucleus as in E-H (±SE).

Figure 1I-L show a complementary data set of spectra revealing the chromatin optical density estimation for HIT and LIT regions in the erythropoietic cells. A sharp light absorbance was observed at 550 nm and may be attributed to the so-called Romanowsky-DNA complex. An increase in the optical density for highly condensed chromatin at 620-680 nm (Figure 1L) correlated with differentiation, as seen for late normoblasts. Therefore, the results show some specific spectral features of chromatin that may be related to differentiation on a subcellular level at a spectral region of 550-720 nm.

Absorbance Images
On the basis of the calculated optical density of the 4 x 104 pixels of each cell, it was possible to reconstruct images defined as "absorbance images" (Figure 2A-D). Chromatin condensation in various erythroid progenitor cells was best expressed by the intensity of light absorption of the nucleus. Thus, the higher the absorbance sites in the nucleus, the more the chromatin was condensed and the cell differentiated.



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Figure 2. (A-D) Reconstruction of absorbance images according to the Beer-Lambert law for each pixel of the images; the order of the cells is as seen in Figure 1. The color of each pixel represents its true absorbance spectral range. (E-H) Spectral similarity mapping of the cells using as reference spectra the HIT absorbance spectra seen in Figure 1. (I-L) Spectral similarity mapping of the cells using as reference spectra the LIT absorbance spectra. Bar = 7 µm.

Similarity Mapping Images
Figure 2E-L reveal nuclear arrays of chromatin in a proerythroblast and in basophilic, polychromatic, and orthochromatic cells, respectively. By using a reference HIT spectra for similarity mapping, it was revealed that the major nuclear area of the proerythroblast is composed of HIT regions arranged in small unconnected patches. HIT regions in the nuclei of basophilic and polychromatic cells (Figure 2E-H) showed a circular symmetry. A central spot was observed surrounded by five or six wing-like regions distributed in a symmetrical fashion. The peripheral chromatin spots were connected to the nuclear envelope margins. The opposite complementary distribution of the LIT regions is seen in Figure 2I-L. The chromatin in the orthochromatic normoblast showed circular patches that may still indicate some ordered distribution. The same distribution has been found to exist in a large number of orthochromatic cells, as shown in Figure 3. Therefore, these spectral map images showed marked differences in chromatin condensation and distribution in the analyzed cells. Table 1 shows the values of chromatin distribution between LIT and HIT areas in differentiating erythroblasts. The LIT values depict a trend of chromatin condensation that starts at 50% of total nuclear area in erythroblasts and reaches 75% in orthochromatophilic cells.



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Figure 3. Spectral similarity mapping of 10 different orthochromatic normoblasts. (A-J) HIT (left column) and LIT (right column) similarity maps for each cell are presented. Bar = 7 µm.


 
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Table 1. Chromatin arrays represented by LIT and HIT areas in nuclei of differentiating cells calculated from similarity map images; each value is the average of 5-9 nuclei ± SE

To determine the nature of the nuclear fragments observed in the erythroid progenitor cells in a case of AMM, we employed scanning electron microscopy (Figure 4A). The nuclear fragments appear as three separate spheres protruding from the cell surface. Transmission electron microscopy of an erythroid progenitor cell (Figure 4B) showed that the nuclear fragments were composed of a circular ring of highly condensed chromatin with an unstained center. The nuclear sorting of PI-stained progenitor red cells from the AMM patient by FACS displayed two populations of cells, one with an intact nucleus in G1-, S-, and G2-phases, and another population with fragmented DNA to the left of the G1-phase cells (Figure 4C). The cell population with fragmented DNA was collected and stained with MGG. The absorbance images of these cells, achieved by spectrally resolved image analysis as shown in Figure 5A-D, reveal a process of chromatin condensation evolving into nuclear fragmentation. Similarity mapping and image reconstruction were carried out by employing two families of spectra, one with a high absorbance peak and the other with a lower absorbance peak at 540 nm. An image of an intact nucleus reconstructed from the low absorbance peak revealed a circular distribution, as shown in Figure 5E. The similarity map of the low-absorbance complex is seen in Figure 5I, in which a circular pattern is depicted. Furthermore, fragmented nuclei showed a symmetrical, circular windmill-like pattern, as shown in Figure 5F and Figure 5J. One can note a spoke-wheel-like pattern at the nuclear periphery, shown as bright spots aimed toward a central region (Figure 5F). The nuclear fragment separated from the main nuclear body encompassed only the peripheral spots. Figure 5J shows the complementary similarity map of the low-absorbance chromatin. Figure 5G and its complementary similarity map image shown in Figure 5K reveal a nuclear fracture in an apoptotic normoblast. Figure 5H and Figure 5I clearly show the final disintegration of the apoptotic normoblast nucleus.



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Figure 4. Characterization of agnogenic myeloid metaplasia red blood cells by electron microscopy and flow cytometry. (A) Scanning electron micrograph of a cell showing nuclear fragments protruding from the cell membrane. Bar = 1 µm. (B) Transmission electron micrograph of a cell showing nuclear apoptotic bodies (arrowheads). Bar = 0.5 µm. (C) Flow cytometry of propidium iodide-stained cells revealing apoptotic cells (AP) to the left of the G1-phase.



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Figure 5. (A-D) Reconstructed absorbance images of agnogenic myeloid metaplasia red blood cells that represent four stages of nuclear fragmentation. The color of each pixel represents its true absorbance spectral range. (E-H) Spectral similarity mapping of the cells using HIT absorbance as reference spectra. (I-L) Spectral similarity mapping of the cells using LIT absorbance as reference spectra. Bar = 6.4 µm.

Principal Component Analysis
Our interpretation of cell structure is biased by our biological education. Because the similarity mapping procedure is based on prior knowledge and identification of the different regions of chromatin, a second, more objective mathematical method was used, known as principal component analysis. Principal component analysis of May-Grunwald-Giemsa-stained cells showed that information is located in the first (largest) five eigenvalues. Each eigenvector was used for the reconstruction of a new image based on that dataset. Figure 6A-F show eigen images of AMM-derived normoblast apoptotic nuclei. The eigen images appear to be identical to the similarity mapping images of the same cells. They depict circular chromatin fragments in which the center is less condensed.



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Figure 6. Principal component analysis of agnogenic myeloid metaplasia red blood cells. The spectra file of each cell was subjected to principal component analysis and the information of eigenvectors 2 and 3 was reconstructed and is presented here. (A-D) Four stages of nuclear fragmentation: circular structures, windmill-like pattern, initial fragmentation, and separated apoptotic bodies obtained from PCA band 2. (E,F) Another view of the same cells as in C and D, obtained by PCA band 3. Bar = 5.7 µm.

The symmetry in the nuclei of both the differentiating erythroblasts and the AMM normoblasts confirms the assumption that chromatin organization is a highly ordered phenomenon.


  Discussion
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Summary
Introduction
Materials and Methods
Results
Discussion
Literature Cited

In 1991, Haaf and Schmid stated that the existence of highly ordered organizational patterns in the cell nucleus appears to be beyond any doubt. It has been proposed that repetitive sequences act as a structural center for the extension and condensation of chromatin (Manuelidis and Borden 1988 ). Therefore, compartmentalization of chromatin could provide a structural framework for efficient processing of nuclear events (Vourc’h et al. 1993 ). On the basis of this hypothesis, the specific nature of the compartmentalization could reflect the physiological state of a given cell (Emmerich et al. 1989 ; Popp et al. 1990 ; Van Dekken et al. 1990 ; Vourc’h et al. 1993 ). However, it should be emphasized that a universally valid principle of chromosome arrangement does not exist (Haaf and Schmid 1991 ).

In the present study, Fourier transform multipixel spectroscopy and spectral imaging were used to resolve the fine nuclear morphology of differentiating and apoptotic erythroid cells stained by May-Grunwald-Giemsa. The nucleus appeared to be composed of two distinct spectral regions, the first exhibiting high intensity transmitted light with a spectral range of 550-750 nm and the second producing low-intensity transmitted spectra with a peak at 680-700 nm. This spectral variance might be explained by the difference in the local components binding the dye, such as chromatin and proteins. Optical density imaging of the cells, obtained by applying the Beer-Lambert law, produced a high-resolution picture emphasizing the difference in absorbance between the nucleus and the cytoplasm. It is well known that cytoplasmic RNA content is reduced during differentiation (Papayannopoulou and Abkowitz 1991 ), which in MGG-stained cells is expressed by a reduction in cytoplasmic absorbance, while the absorbance of the nucleus increases with chromatin condensation.

The similarity mapping procedure applied in the present study assisted in distinguishing between the different nuclear regions that were found to exhibit symmetrical patterns of circular and windmill-like rearrangements accompanying differentiation. The application of an objective mathematical algorithm for spectral image analysis, known as principal component analysis, revealed the same windmill-like structural features and symmetry. Furthermore, normoblasts in the peripheral blood of an AMM patient exhibited highly ordered condensation and fragmentation of the nuclei, characteristic of apoptosis. The applied mathematical algorithms for image analysis revealed a symmetrical breakage of the nucleus during apoptosis, with each fragment being one piece of the intact windmill pattern. Deckwerth and Johnson 1993 have shown that, in cell cultures, the appearance of apoptotic nuclear changes is linked biochemically to internucleosomal DNA cleavage, detectable as a "ladder" after electrophoresis on an agarose gel.

The idea of territorial organization of chromosomes was first proposed at the turn of this century by Rabl 1885 , Strasburger 1905 , and Boveri 1909 . Most scientists believed that chromosomes were temporary structures formed de novo at the beginning of mitosis and then dissolved in the daughter nuclei. Rabl 1885 predicted that chromosomes retain structural integrity, and Boveri 1909 speculated on genetic identity throughout the cell cycle. Boveri 1909 postulated that each chromosomal territory would occupy a specific region of the nucleus, maintaining its own coherence and not mixing with the other territories.

Electron microscopic techniques during the 1960s and early 1970s failed to distinguish the hypothetical chromosome territories (Wischnitzer 1973 ). Two decades ago the nucleus was still viewed by many cell biologists and biochemists as a bag with chromatin fibers from the different chromosomes intermingling in the nucleoplasm like "spaghetti in a soup." Now, as a result of the development and technical advances of in situ methods, individual chromosomes or chromosome regions can be visualized directly inside the nucleus and their positions can be followed throughout the entire cell cycle. In situ hybridizations of chromosome-specific DNA, immunofluorescence and electron microscopy, three-dimensional reconstruction, and high-resolution in situ autoradiography have been successfully employed to study the spatial and functional organization of the interphase nucleus (Haaf and Schmid 1991 ). Recently, Cremer et al. 1993 proposed a model predicting that the surface of chromosome territories and a space formed between them provide a network-like three-dimensional nuclear compartment for gene expression, mRNA splicing, and transport, termed the interchromosome domain (ICD) compartment (Zirbel et al. 1993 ).

On the basis of the present results, we speculate that the circular and windmill patterns revealed by spectrally resolved imaging define a three-dimensional compartmentalization of chromatin in the differentiating nucleus. The high-intensity light transmittance regions creating the windmill pattern may represent the interchromosome domain (ICD) compartment of Zirbel (Zirbel et al. 1993 ), while the low-intensity transmittance regions represent the chromatin. According to the model proposed by Cremer et al. 1993 , chromatin loops with genes that are permanently or intermittently expressed in a given cell type should be located at or close to the surface area of each chromosome territory. This arrangement enables RNA transcripts to be directly released into the ICD compartment, to go through processing in a topologically highly ordered manner, and to be transported to the nuclear pores (Carter et al. 1993 ; Xing et al. 1993 ).

The symmetry observed in the nuclei may be maintained by electric forces. According to Cremer et al. 1993 , short-range (nm distances) and long-range (µm distances) electric forces resulting from charge distribution effects of chromosome territories and other nuclear components may be involved in the maintenance of the ICD compartment. Bier et al. 1989 , in their experiments with isolated metaphase chromosomes in suspension under a variety of buffer conditions, have indicated an electric mobility of chromosomes on the order of u = 1 x 10-8 m2/Vsec, indicating an electric net charge of one to several thousand elementary charges, depending on the chromosome size. Assuming that chromosome territories have a similar electric net charge as metaphase chromosomes, the possibility is considered that repulsive Debye-Huckel forces between the surfaces of neighboring chromosomal territories are sufficient to maintain an ICD space of adequate width (Cremer et al. 1993 ). A new model of genome architecture in human sperm cells was presented by Zalensky et al. 1995 , positioning chromosome telomeres in the periphery of the nucleus while centromeres were located in the center. One major question remains unanswered. How do the chromosomes, with their variety of sizes, organize in the nucleus to create such a perfectly symmetrical structure?

The systematizing of chromatin organization in differentiating cells and in abnormal conditions can be regarded as the most reliable tool for cytology and pathological histology. An attempt to analyze the three-dimensional nuclear structure of breast carcinomas and to correlate it with patient prognosis in a retrospective study has proved to be highly significant compared to standard histological classification (Komitowski et al. 1993 ). It was concluded that the relevance of chromatin organization in the cancer cell, compared with staging and patient survival, is a markedly better prognostic tool than these other criteria. Because spectral image analysis provides objective data of chromatin stain complexes and highlights new aspects of extant structures within the nucleus, we believe that it may serve as a diagnostic tool. Recently we have developed the concept of spectral morphometry by which the nuclear components as well as cytoplasm can be resolved on the basis of spectral similarity mapping. Spectral morphometry will be used for classification of transformed vs normal cells in combination with classical morphometry.


  Acknowledgments

Supported by a grant from Applied Spectral Imaging, Migdal HaEmek, Israel.

We gratefully thank Ms Judith Hanania for assistance in editing the manuscript and Mr Avi Haris, Mr Jacob Langsam, and Dr Orit Katzir for their skillful assistance.

Received for publication October 21, 1996; accepted February 24, 1997.


  Literature Cited
Top
Summary
Introduction
Materials and Methods
Results
Discussion
Literature Cited

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