However, the staining protocol is comparatively longer and is more laborious compared to using DAPI. Before At present single-cell surface marker/RNA sequencing (scRNA-Seq) is the accepted method to identify the intermediate states that occur during EMT in metastasis. and transmitted securely. Changes in nuclear texture occur in conjunction with other morphological variations such as nuclear and nucleolar size, shape and count at the tissue level and the organisation of protein content, based on which cancerous cells are differentiated from normal ones2,7. Dahl, K. N. & Luxton, G. G. A special topic on nuclear mechanobiology. Cells must be permeabilized and/or fixed for DAPI to enter the cell and to bind DNA. Intell. Liu, L., Fieguth, P., Kuang, G. & Zha, H. Sorted random projections for robust texture classification. For the PC3 data set, on the other hand, there is a decrease in the intensity and HC aggregation, which signifies a decondensation or open chromatin state on the transition to the EMT state (see Supplementary Figs. It has outperformed commonly used, diverse variants of 3D texture descriptors such as Moments, Haralick, Tamura, Gabor and other variants of LBP for cell classification13,21,22. Int. The resultant vectors \([f_{G}]_{CP_{yz}}, [f_{C}]_{CP_{yz}}, [f_{S}]_{CP_{yz}}, [f_{A}]_{CP_{yz}}, [f_{R}]_{CP_{yz}}\) (CP stands for cubic patch) are each normalised into 16 bin histograms and combined to represent the SRP descriptor of the YZ plane of a cubic patch with dimension 80 (16 bins \(\times\) 5 functions): This process is repeated for the XZ plane as well. Results show that 3D SRP and 3D Local Binary Pattern provide better classification results than other feature descriptors. School of Computer Science and Engineering, University of New South Wales, Sydney, NSW, Australia, Priyanka Rana,Arcot Sowmya,Erik Meijering&Yang Song, Graduate School of Biomedical Engineering, University of New South Wales, Sydney, NSW, Australia, You can also search for this author in DAPI staining and DNA content estimation of nuclei in uncultivable Majtner, T. & Svoboda, D. Comparison of 3d texture-based image descriptors in fluorescence microscopy. Classification models are also compared statistically for their metric values. The lifetime of DAPI bound to interphase chromosomes within a 3:1 methanol:acetic acid fixed nucleus from the GM18507 lymphocyte cell line was also imaged, as shown in Fig. Vital staining of nucleus is a useful method in plant cell culture and protoplast fusion studies. Chromosoma 121, 527538 (2012). A simple-to-use fluorescent stain, 4,6-diamidino-2-phenylindole (DAPI), visualizes nuclear DNA in both living and fixed cells. Cancer 4, 677687 (2004). Images are preprocessed following quality protocols and segmented to obtain individual cells with minimal background. Hence following BOVW, feature vectors of cubic patches from all volumetric images are clustered to generate a visual vocabulary of the most informative and dominant features by utilising k-means and sum pooling (details in the Feature representation section). D1306,D3571,D21490,S33025,10010023,P36930, P36934,S36936,S36937, Copyright 2006-2023 Thermo Fisher Scientific Inc. All rights reserved, Spectroscopy, Elemental and Isotope Analysis, Adherent cells for fluorescence microscopy, Properties of classic nucleic acid stainsTable 8.4, Barcellona ML, Cardiel G, Gratton E (1990), Tanious FA, Veal JM, Buczak H, et al. Use the fixation protocol appropriate for your sample. sharing sensitive information, make sure youre on a federal As a first step, segmentation of individual cell nuclei from potentially noisy microscopic images is performed before classification. Both DAPI and Hoechst are minor-groove binding dyes with a preference for A/T-rich regions of DNA over G/C-rich DNA. The results also suggest that heterochromatin undergoes considerable change in intensity and aggregation on the transition from normal to another phenotypic state in fibroblast and PC3 cells. Phys. 4'6 Diamidino-2-phenylindole (Dapi) - Jstor The ImageNet pretrained VGG-16 model has established itself as a reliable choice in biomedical studies43. 142, 2336 (2016). IEEE Trans. 42, 6088 (2017). Labeling nuclear DNA using DAPI - PubMed With VGG-16 (a CNN model trained on ImageNet), the input image goes through a series of convolutional layers before it finally produces a dense set of local feature descriptors of 512 dimensions at the last fully convolutional layer. Overall performance evaluation implies that 3D SRP and 3D LBP performed better than all other considered handcrafted feature descriptors, while 3D SRP achieved better results than 3D LBP for the PC3 data set. A. et al. F1 scores for most of the feature descriptors are good for the PC3 data set with a high number of slices (Fig. IEEE Trans. As illustrated in Fig. CAS In International Workshop on Combinatorial Image Analysis, Lecture Notes in Computer Science, Vol. Disclaimer. Rep. 7, 113 (2017). Provided by the Springer Nature SharedIt content-sharing initiative. Giemsa staining of preparations identical to those stained with DAPI resulted in equivalent parasitemia (data . Stoklasa, R. & Majtner, T. Texture analysis of 3d fluorescence microscopy images using rsurf 3d features. While the usual practice to obtain CNN features in biomedical studies is by training a new CNN model, the available number of images poses a limitation on training an optimal CNN. Even though images in EMT class consist of cells with diverse characteristics, good classification results are still achieved because of feature representation techniques (BOVW and FV), which derive new image features corresponding to the most dominant original features of the whole data set. Due to parameter setting for the Otsu algorithm, objects with very low intensity could not be identified in a few top-most and bottom-most slices, resulting in final object thickness up to 15 slices for fibroblast cells and 60 for PC3 cells. J. Electron. Imaging 13, 146166 (2004). SRP is based on the dimensionality-reduction technique known as Random Projections (RP), which compresses high dimensional data, captures salient information without information loss and preserves inter-distance of data values while projecting to a lower dimensional space. A number of fluorescent stains are available that label DNA and allow easy visualization of the nucleus in interphase cells and chromosomes in mitotic cells, including Hoechst, 4',6-diamidino-2-phenylindole (DAPI), ethidium bromide, propidium iodide, and acridine orange. 3d cell nuclear morphology: Microscopy imaging dataset and voxel-based morphometry classification results. The voxel size of all volumetric images from both sets is \(0.1318 \times 0.1318 \times 1\) \(\upmu {\text{ m }}^3\). DAPI staining and DNA content estimation of uncultivable microbial In addition, image analysis software was used to estimate the DNA content in the nuclei of Arcellinida and ciliates, and the measurements of target organisms were compared to those of well-known model . The dataset also includes meta-data extracted from the original data. This is represented as. Med. 5c, multiple hyperplanes are generated between each column of the bottom-most slice and columns of the top-most slice in a cubic patch. \end{aligned}$$, $$\begin{aligned} \textit{Null hypothesis }{H_0}= \textit{Pseudo 3D outperforms 3D.} CellProfiler, being a highly sensitive tool, has discarded comparatively more PROLIF cell objects, based on applied quality protocols. & Shilatifard, A. Chromatin signatures of cancer. Article A. Kalinin, A. 4 and Supplementary Figs. A comparison of the achieved segmentation results with the SOTA works10,11 on the same dataset is provided in Supplementary Table S1. All cell images have three channels showing different fluorophores: DAPI stain for nuclei, fibrillarin antibody (anti-fibrillarin) and ethidium bromide (EtBr) for staining nucleoli. Zink, D., Fischer, A. H. & Nickerson, J. Estimation of three-dimensional chromatin morphology for nuclear classification and characterisation, $$\begin{aligned} \textit{Null hypothesis }{H_0}= \textit{All classification models have the same mean rank.} It is a rotationally invariant texture feature descriptor and has achieved competitive results and efficiency. Estimation of three-dimensional chromatin morphology for nuclear classification and characterisation. Along with the earlier mentioned handcrafted features (SIFT, LBP and RSurf), Convolutional Neural Networks (CNNs)24 are also used to generate deep learning features for comparison. Choosing the kernel parameters for support vector machines by the inter-cluster distance in the feature space. Following a standard cross-validation setup46, in each iteration, one subset is held out for model testing (an independent test set), and the remaining nine subsets are used to train the model (outer training set). In this study, we developed protocols for DAPI (4',6-diamidino-2-phenylindole) staining of Arcellinida nuclei and adapted protocols for ciliates. Bookshelf Bone texture characterization with fisher encoding of local descriptors. The significance of including third plane information for low-resolution volumetric images is also investigated by comparing the performance of 3D texture descriptor with its respective pseudo 3D form that ignores the interslice intensity correlations. Characterization of brain cell nuclei with decondensed chromatin Nuclear structure in cancer cells. Internet Explorer). Uhler, C. & Shivashankar, G. Nuclear mechanopathology and cancer diagnosis. Nat. Article Careers. However, all other subsamples performed as well as 3D SRP and 3D LBP. Subsequently, each 3D image is represented by the visual vocabulary word that is identified based on the closest distance between the image feature and visual words in the codebook. Radhakrishnan, A., Damodaran, K., Soylemezoglu, A. C., Uhler, C. & Shivashankar, G. Machine learning for nuclear mechano-morphometric biomarkers in cancer diagnosis. and Y.S. ROC curves: 3D SRP vs Pseudo 3D SRP (a) Fibroblast dataset. DAPI staining (blue) depicts the nucleus with an intranuclear inclusion, which contains the autophagy-associated proteins ubiquitin and p62. The current implementation of BOVW utilises k-means clustering for codebook generation, an unsupervised learning algorithm to generate the visual vocabulary as clusters, and sum pooling to quantise the image in the form of a histogram vector. eCollection 2023 Jul. Their study discarded connected cell objects; however, this study employed a semi-automated approach where results from CellProfiler are visually inspected, and the watershed algorithm is applied to segment connected cell objects, leading to a higher number of SS, EMT and EPI cell objects. J. 9, 203206 (2016). Its blue fluorescence stands out in vivid contrast to green, yellow, or red fluorescent probes of other structures. 1995 Sep;70(5):220-33. doi: 10.3109/10520299509108199. DAPI (pronounced 'DAPPY', /dpi/), or 4,6-diamidino-2-phenylindole, is a fluorescent stain that binds strongly to adenine-thymine-rich regions in DNA.It is used extensively in fluorescence microscopy.As DAPI can pass through an intact cell membrane, it can be used to stain both live and fixed cells, though it passes through the membrane less efficiently in live cells and therefore . DAPI is a popular nuclear counterstain for use in multicolor fluorescent techniques. The proposed approach includes third plane information using hyperplanes into the design of the Sorted Random Projections (SRP) texture feature and is evaluated on publicly available 3D image datasets of human fibroblast and human prostate cancer cell lines obtained from the Statistics Online Computational Resource. Bonaccorsi S, Giansanti MG, Cenci G, Gatti M. Cold Spring Harb Protoc. FOIA For most nucleic acid stains, the fluorescent signal is minimal before binding to DNA or RNA, and there is a significant increase in fluorescence intensity after the dye has bound to DNA or RNA. S3c). Slices from the volumetric image are extracted using ImageJ35 and fed into CellProfiler36. The .gov means its official. Bethesda, MD 20894, Web Policies Unlike other texture descriptors utilised in this study, there is currently no 3D version of SRP. 23, R1113R1121 (2013). P.R. The two-sided Wilcoxon rank-sum test at the significance level of 1% is utilised to measure the difference in \(HC/EC_{PixelValues}\) and \(HC/EC_{PixelDifferences}\) between two classes for both cell lines. At the molecular level, alterations appear as a change in nuclear texture formed by wrinkles, folds and trenches manifested through entwined strands of nuclear proteins, lamins and chromatin. The nucleus, being a prominent organelle of eukaryotic cells, houses cellular DNA (chromatin), hosts chromosome formation and offers a dynamic research domain to measure and study nuclear. An ovol2-zeb1 mutual inhibitory circuit governs bidirectional and multi-step transition between epithelial and mesenchymal states. J Microsc. Corresponding to the high luminance contrast regions in DAPI images, in previous studies HC is identified by applying a threshold equal to the sum of the minimum intensity and sixty per cent of the difference between the maximum and minimum intensities9. The hypothesis for the KruskalWallis test is: ROC curves for all feature descriptors. Carefully remove the coverslip and rinse the specimen briefly with PBS or dH. As evident from earlier studies10,11 on the same dataset, G0/G1 Serum Starvation Protocol imposes significant changes in cell size and shape, which refer to changes in lamins, the protein primarily responsible for nuclear size and shape. This FV encoding is applied to the deep learning (CNN) features, and the resultant dimension of FV-CNN is 65536 (\(2 \times 64 \times 512\)). Cellular alterations at the molecular level may happen inconsistently in a small group of defective cells in a tissue microenvironment. Sections were mounted on Histobond glass slides (Marienfeld), fixed in 4.5% formaledhyde and stained with 4,6-diamino-2-phenylindole (DAPI), a blue fluorescent dye conventionally used for staining . DAPI staining and DNA content estimation of nuclei in uncultivable The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. \end{array}\right. } This site needs JavaScript to work properly. DAPI (4,6-diamidino-2-phenylindole) is a blue-fluorescent DNA stain that exhibits ~20-fold enhancement of fluorescence upon binding to AT regions of dsDNA. Density imaging of heterochromatin in live cells using orientation-independent-dic microscopy. SRP. 6. Cell 28, 33493359 (2017). In this study 3D Cell Nuclear Morphology Microscopy Imaging Dataset is used; the largest available public 3D image set obtained from Statistics Online Computational Resource (SOCR)10,11. A survey on deep learning in medical image analysis. 16, 021001 (2019). Biol. Epub 2023 Jan 24. Cooper J, Um IH, Arandjelovi O, Harrison DJ. in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops 22722280, (2018). In the early years of 3D texture description, Gray-Level Co-Occurrence Matrix (GLCM) descriptors were widely used for fluorescence microscopy images19. Song, Y. etal. 34, 574586 (2012). In addition, image analysis software was used to estimate the DNA content in the nuclei of Arcellinida and ciliates and to compare them to measurements of well-known model organisms. Rep. 6, 31417 (2016). rocyte nucleus, and free merozoites (m) could also be observed. designed the methodology. When downregulation of gene expressions occurs, some of the euchromatin changes to heterochromatin that makes the segments of DNA more compact (DNA methylation)28. However, the inference remains the same for the pixel differences approach and no statistical significance in ratio difference is found for the pixel value method. HC intensity measure HC/EC ratio based on pixel values estimates the fraction of the HC intensity in the nucleus. (7). DAPI staining solution: dissolve 1 mg of 4,6-diamidino-2-phenylindole (DAPI, Sigma #D9542) in 1 ml of water, filter-sterilise and store 100 l aliquots at 20 C. Lymphocyte Classification from Hoechst Stained Slides with Deep Learning. It is defined by five functions computed by accessing image pixels in a global, circular and square pattern, and pixel differences in an angular and radial pattern. HC/EC ratios were also computed following the pseudo 3D approach. The phylogenetic analysis based on the 18S rRNA gene sequence shows that this species belongs to the clade of . To study the impact of computing third plane information for low resolution, 3D versions of SIFT, LBP, RSurf and SRP was compared with their corresponding pseudo forms that ignores the interslice intensity correlations. Unable to load your collection due to an error, Unable to load your delegates due to an error. 27, 335345 (2005). Humphrey, J. D., Dufresne, E. R. & Schwartz, M. A. Mechanotransduction and extracellular matrix homeostasis. Vision Image Understand. Protocol: Staining Cells with Hoechst or DAPI Nuclear Stains 26, 49004910 (2017). Thermo Fisher Scientific. EMT cells with their ICS are of high importance in studies related to comprehension of cancer progression and drug resistance. Dilute the DAPI stock solution to 3 M in staining buffer (100 mM Tris, pH 7.4, 150 mM NaCl, 1 mM CaCl. At 1% significance level and very small p-value (< 0.01), the Kruskal-Wallis test indicates the difference between mean ranks of five groups (SRP, LBP, SIFT, RSurf, FV-CNN). Pipeline to classify cellular phenotypic states and measure chromatin patterns. Although these alterations have been a gold standard for late-stage diagnosis of tumours, the description of their origin, interdependency and progression is not clear; therefore early diagnosis of cancer, drug discovery and prognosis care remains a challenge2,7,9. Article \({x}^{Glob}\) is obtained by sorting all the pixels of the patch. Cell. Furthermore, two different cellular states in EMT class are identified and characterised, which are considered to hold critical biological significance when studying cancer progression and drug resistance. DAPI Counterstaining Protocols | Thermo Fisher Scientific - US ACM 60, 8490 (2017). Epub 2014 May 15. Why is the nucleolus so important? 11) and adjacent pixel differences (Eq. Values from each ring are sorted, concatenated and projected to a lower dimensional space while preserving the original distances between data points14. Examination of nuclei morphology by fluorescent staining. Being a profoundly condensed and compact chromatin fraction, it is easily detectable by DAPI staining30,31. DAPI staining carried out following the Hyalosphenia protocol. Note that the utilised data set has multiple subsets of images for each class where each subset represents one run of the microscope of different cell samples. 8466, 186195 (Springer, 2014). Muiz-Buenrostro A, Arce-Mendoza AY, Montes-Zapata EI, Caldern-Melndez RC, Vaquera-Alfaro HA, Huerta-Polina JA, Montelongo-Rodrguez MJ. \end{aligned}$$, $$\begin{aligned} {H_{0\_Fibroblast}}= & {} \textit{Normal cell state has higher HC/EC than another phenotypic state} \end{aligned}$$, $$\begin{aligned} {H_{0\_PC3}}= & {} \textit{Normal cell state has lower HC/EC than another phenotypic state.} 3b). Abstract A simple-to-use fluorescent stain, 4',6-diamidino-2-phenylindole (DAPI), visualizes nuclear DNA in both living and fixed cells. official website and that any information you provide is encrypted The choice of LBP and SIFT is also motivated from a recent review of texture descriptors that mentions SIFT and LBP as milestone texture feature descriptors15. Image Anal. To make a concentrated stock solution, dissolve in H 2 O up to 5 mg/mL. \(EMT*\) refers to the image set without \(EMT^{179}\). This protocol presents two different fixation methods for DAPI staining: ethanol fixation and . A graph of SSE for each value of k is plotted, which usually takes the shape of an arm, and the value of k corresponding to the elbow of the arm is chosen as an optimal value which represents the least value of k after which SSE scarcely varies. doi: 10.1101/pdb.prot067363. Recent developments in confocal microscopy have enabled more effective in-vivo intraoperative studies through 3D fluorescence images, to analyse the heterogeneity of cellular patterns16. Each volumetric image of both cell lines is in 3D TIFF format and has dimensions \(1024 \times 1024 \times Z\) voxels, where Z ranges from 30 to 40 slices in the fibroblast cell collection and 6580 slices in the PC3 cell collection. Imagej 2: Imagej for the next generation of scientific image data. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate. Commun Med (Lond). J. Biomol. Deep Active Learning for Automatic Mitotic Cell Detection on HEp-2 Specimen Medical Images. Leave the cells in ethanol at -20C for 5-15 minutes. Cellular changes at the molecular level can be understood through an adequate feature description capable of capturing low-level details of cells in multi-dimensions. The current implementation generates G=64 Gaussian components from patch-level features.