toward a 'visible cell'… and beyond · 2016-07-13 · from the cover: böhm et al....

TOWARD A ' V I S IBLE CELL '… AND BEYOND

IntroductionElucidating the three-dimensional (3D) fine structure of

molecules, cells and tissues is pivotal to the development of a complete understanding of basic cell and molecular biology, and thus requisite to successfully translating that knowledge to efficacious clinical application and therapeutic intervention in the prevention and/or treatment of disease. If current efforts are successful with respect to integrating data related to the 3D structure-function relationships that underpin intra- and inter-cellular interactions, networks and signalling − from molecule-to-cell and from cell-to-tissue − new generations of biologists will benefit from a more 'holistic' understanding of molecular organisation and biochemistry in situ.

One such effort with an underlying focus on mammalian cell imaging is the Visible CellTM Project, based at the Institute for Molecular Bioscience and the ARC Centre in Bioinformatics at the University of Queensland. Over the past three years, this program has evolved beyond what was originally simply an ambitious undertaking in structural cell biology, that is, to reconstruct entire mammalian cells in 3D at the electron microscopy (EM) level with sufficient resolution to distinguish all subcellular compartments and filaments of interest at once. The program has matured into what is now a large-scale, cross-disciplinary and multi-institutional initiative that ultimately aims to provide a computational and visualisation framework with which to explore mathematical models embedded onto real 3D cellular structure data obtained from mammalian cells using a

variety of imaging methods, including high-resolution 3D imaging techniques such as cellular electron tomography (ET) (1,2). Indeed, the Visible CellTM Project has already been described by Professor Anne Trefethen (former Deputy Director of the UK's e-Science Core Program) as a new way of doing biological science, and the program has been held up as an exemplar of e-research in Australia [www.arc.gov.au/pdf/e-Research_slides3.pdf].

Background and SignificanceThe first incarnation of a 'Visible Cell' per se arose from

work carried out at the Boulder Laboratory for 3D Electron Microscopy of Cells, a National Biomedical Technology Research Resource originally established through the National Institutes of Health in the US so that one of the 'founding fathers' of cell biology − Keith Porter − could pursue the use of higher accelerating voltages for imaging whole cells by EM. Over half a century after the images from Porter's seminal publication had demonstrated the power of the EM to clearly resolve cellular fine structure in mammalian cells and consequently revolutionised the study of mammalian cell biology forever (3), a single high-resolution 3D tomographic reconstruction of the Golgi region in an insulin-secreting beta cell derived from the 'islets of Langerhans' of the endocrine pancreas (Fig. 1) provided new and unanticipated insights into 3D cellular organisation that has impacted substantially on how scientists, students and the public alike picture life at the subcellular level (Fig. 2) (4,5).

Brad Marsh1,2*1Institute for Molecular Bioscience, University of Queensland, QLD 4072

2Centre for Microscopy & Microanalysis and School of Molecular & Microbial Sciences, University of Queensland, QLD 4072

*Corresponding author: [email protected]

Spe c ia l Te chn i ca l Fea ture

Vol 37 No 3 December 2006 AUSTRALIAN BIOCHEMIST Page 5

Fig. 1. A 3D reconstruction of an intact pancreatic 'islet' isolated from rodent pancreas and imaged by multi-colour immunofluorescence confocal laser scanning microscopy.Shown are the glucagon-secreting alpha cells (blue), somatostatin-secreting delta cells (mauve) and insulin-secreting beta cells (green). Reproduced with permission from Robert Sorenson, Department of Genetics, Cell Biology and Development, University of Minnesota Medical School, USA (17)


ET uses mathematical techniques to computationally reconstruct a 3D volume from a set of accurately aligned two-dimensional (2D) images collected in the EM as the specimen is serially tilted by small, regular increments (e.g. 1° or 1.5°) over a relatively large angular tilt range (e.g. ±60-70°). Because the resolution of an object within the plane of the specimen with a slab geometry − such as a thick slice ('section') cut from plastic-embedded cells and/or tissue − also depends on its orientation relative to the axis around which the specimen is tilted, cellular 'tilt series' data are often collected around a second tilt axis orthogonal to the first for improved resolution and symmetry of cellular structures in 3D in the final 'dual-axis' tomographic reconstruction (1). Cellular ET in particular has emerged as a powerful method for obtaining useful 3D structural information about cells and organelles at resolutions that typically range between 5 and 10 nm, thus providing a 'resolution bridge' for studying molecular cell biology in situ.

However, although ET is now almost considered a mainstream research tool on many campuses globally, including the University of Queensland, the significant challenges associated with tomographic reconstruction of large cell volumes at high-resolution has restricted serious attempts to generate accurate 3D cell atlases to just a handful of groups worldwide (1,6). By way of example, although the reconstructed region presented in Fig. 2 was estimated to encompass only around 1% of that cell's total volume, the technical significance as well as biomedical relevance of the work remains a hallmark of the US National Resource where it was carried out [http://www.ncrr.nih.gov/ncrrprog/btdir/Microsco.asp#finest].

Nonetheless, spurred on by the National Library of Medicine's 'The Visible Human Project®' [http://www.nlm.nih.gov/research/visible/visible_human.html] which created the first 3D atlases of entire human cadavers using a combination of computed

Fig. 2. A 3D model of the Golgi region in an insulin-secreting rodent pancreatic beta cell.From Marsh et al. (2001) Organellar relationships in the Golgi region of the pancreatic beta cell line, HIT-T15, visualized by high-resolution electron tomography. Proc. Natl. Acad. Sci. USA 98, 2399-2406.Three serial 400 nm-thick sections cut from a high-pressure frozen, freeze-substituted and plastic-embedded HIT-T15 cell were reconstructed by cellular ET, and all visible objects within the resulting reconstructed volume (3.1 x 3.2 x 1.2 µm3) were manually defined or 'segmented'. The Golgi complex with its seven cisternae (C1-C7) is at the center: C1 (light blue), C2 (pink), C3 (cherry red), C4 (green), C5 (dark blue), C6 (gold), C7 (bright red). The Golgi is displayed in the context of all surrounding organelles, vesicles, ribosomes, and microtubules: ER (yellow), membrane-bound ribosomes (blue), free ribosomes (orange), microtubules (bright green), dense-core vesicles (bright blue), clathrin-negative vesicles (white), clathrin-positive compartments and vesicles (bright red), clathrin-negative compartments and vesicles (purple), mitochondria (dark green). Two model views of the Golgi region rotated 180° around the vertical axis are displayed. Copyright 2001 National Academy of Sciences, USA.

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tomography (CT), magnetic resonance (MR) and serial cryo-section imaging (7) − and is now considered a US national resource in its own right − interest has continued to grow for the development of methods that would allow mammalian cells to be imaged then reconstructed in toto in 3D by ET. Indeed, much of the drive and enthusiasm for the creation of Visible CellTM atlases in 3D at ~5 nm resolution has stemmed from an emerging desire and need within the international cell biology and bioinformatics communities to understand the bigger picture with respect to cells as complex systems. Starting with a precise spatial framework is considered by many in systems biology as a fundamental prerequisite to developing the capacity to realistically and accurately predict changes in the spatio-temporal coordinates of complex molecular and membrane trafficking events in silico (2,8,9).

Visible Proteomics and the Eukaryotic Cell3D reconstructions of cells by ET at high-resolution have

been described as '3D images of the entire proteome of the cell' (10,11). The term 'visual proteomics' − aptly coined by Stephan Nickell and colleagues at the Max Planck Institute for Biochemistry in Martinsried, Germany (6) − has already started to gain favour within the systems biology as well as molecular microscopy communities (8,9). For obvious reasons, a number of major international efforts have been launched to reconstruct entire cells at near-molecular resolution since the proof-of-principle demonstration that macromolecular complexes can be detected and identified in situ in tomographic reconstructions by virtue of their 3D structural 'signature' alone (Fig. 3) (12,13). However, for a variety of reasons these projects have focused almost exclusively on prokaryotic cells that more or less lend themselves to the methods, in stark contrast to most

Fig. 3. Template matching applied to electron tomograms.From the cover: Böhm et al. (2000) Toward detecting and identifying macromolecules in a cellular context: template matching applied to electron tomograms. Proc. Natl. Acad. Sci. USA. 97, 14245-14250. ET currently remains the only technique capable of reproducibly providing 3D subcellular data within the resolution range of 5-10 nm, with convincing prospects for the reproducible generation of cellular tomograms at resolutions better than 5 nm on the immediate horizon. Thus, at least for the foreseeable future, it remains the only method available for mapping the 3D territorial distribution of macromolecules in situ in a close-to-native environment. The structural signatures of macromolecules can be visualised in tomographic slices from 3D cellular reconstructions as black etchings on a background of gray density. Using a technique referred to as 'template matching', this pioneering work from the group of Wolfgang Baumeister demonstrated that in principle the location of macromolecules such as the thermosome and the 20S proteasome (shown on the left and right hand sides, respectively, at 8 nm, 4 nm and 2 nm, viewed from back to front) could be identified within tomograms by virtue of their structural signature alone. Copyright 2000 National Academy of Sciences, USA.



mammalian cells. Even where research groups have set out to reconstruct eukaryotic cells by ET, they have so far confined their attempts to simple eukaryotes (14).We envisage an important biomedical goal of

accomplishing the same task for mammalian cells, whose structure when mapped in 3D at high resolution may inform efforts in public health. The first 'Visible Human Dataset' created by Vic Spitzer and colleagues at the Center for Human Simulation at the University of Colorado [http://www.uchsc.edu/sm/chs/] garnered as much attention and curiosity from the public due to its enormous educational and visual appeal as it did from the biomedical research and surgical communities because of the wealth of fundamental scientific information it encompassed (15). By analogy, in addition to serving as a platform for 3D computer simulations of mammalian cell

'behaviour', a high resolution 3D atlas of even a single mammalian cell in its entirety would in its own right provide profound advances in our understanding and appreciation of cellular architecture and organisation as it relates to function when visualised in toto, particularly in the context of providing unique insights into the basic unit cell as a model for the study of complex systems biology (6,8,9). Initially, we envisage that a Visible Cell atlas will play a high-profile role in scientific educational outreach at both the national and international levels − by providing a quantum leap in terms of how scientists, students and the public alike picture life at the subcellular level in mammalian cells (5). This would have added value if the cell type chosen for such a study had immediate biomedical and/or clinical relevance as well as fundamental scientific value at the basic science level.


Fig. 4. The application of semi-automated tools for pre-processing and 3D segmentation of tomograms generated by cellular ET.The most time-consuming portion of cellular ET currently resides at the level of detailed 3D image analysis, i.e. having to manually delineate or 'segment' membrane-bound compartments and other objects of interest at the subcellular level. However, preliminary efforts towards the development and application of fast and accurate automated methods for detecting and segmenting 3D cellular data, in a manner analogous to the complex 3D algorithms routinely used to segment EM density maps of 3D molecular structure data (16), have already proved fruitful. Typically, cellular ET data require some additional image 'pre-processing' to help the 'signal' of interest (e.g. membranes, filaments, vesicles) to stand out against a sea of 'noise' in the background (e.g. cytoplasmic density). In a mathematical context, this enhancement of signal-to-noise generally improves the performance of algorithms designed to accurately detect and define structures of interest. (a) A tomographic slice is presented from the original reconstruction of one of the 400 nm-thick plastic sections from which the surface-rendered 3D model shown in Fig. 2 was generated. (b) The same tomogram was pre-processed with a three-pass iterative 3D median filtering algorithm that efficiently denoises the image data while preserving the location of edges and enhancing contrast. In the example of semi-automated segmentation using a novel 3D variant of the watershed transform (c-f), a slice of the original tomogram is shown at the far left (c). In (d), the raw outcome of an application of the 3D watershed algorithm after pre-processing with a spatial averaging routine is overlaid on the original, unfiltered data for reference, with very few falsely assigned structures evident. These can be easily identified/eliminated during post-processing. (e) The segmentation after cleanup. Some of the features display reversed contrast and can only be segmented correctly if this is taken into account. (f) The combined result of the two segmentation runs with contrast reversal (first, black border; second, white border) showing that practically all membrane-bound structures are identified and most of them are well delineated.(a-b) Reproduced with permission from Niels Volkmann. (c-f) Reprinted from Fig. 6, first published in 'A novel three-dimensional variant of the watershed transform for segmentation of electron density maps' by Niels Volkmann, J. Struct. Biol. (2002) 138, 123-129, copyright Elsevier (16).


The Visible Insulin-Secreting Beta CellTo this end, we have undertaken a multi-

resolution/multi-throughput approach toward reconstructing mammalian cells in 3D at the EM level. Our group's primary research remains focused on elucidating key structure-function relationships related to the biosynthesis, processing and trafficking of insulin under normal versus abnormal conditions in beta cells still resident in situ within intact pancreatic islets (Fig. 1) isolated from mice and humans. Complementary to these high-throughput/high-resolution studies of the key organelles involved in insulin manufacture and exocytosis, two separate yet overlapping projects aimed at developing methods for imaging whole pancreatic beta cells at different resolutions are currently well underway in our laboratory; these projects reside at the very heart of the Visible CellTM Project. Each in its own way will provide crucial scaffold data essential for setting up interactive platforms for computational dissection of structure-function changes in silico.The first of these two projects aims to reconstruct and

segment an arbitrary volume (~400 µm3) of a single beta cell by ET at approximately 5 nm resolution as proof-of-concept. This project requires the development of novel methods at almost every level, from efficient and precise image acquisition, 3D reconstruction, segmentation and navigation to data warehousing, management, archiving and retrieval. Moreover, even though this proof-of-concept dataset represents only a fraction (~10%) of the data that will be required to reconstruct a whole cell in 3D at high resolution, it remains an incredible volume of raw 3D cellular data (i.e. approximately 1 TB) and itself represents a grand challenge in high-throughput ET, since it will equate to around 405 'normal' high resolution tomograms when complete. Consequently, the successful analysis of this enormous volume demands the concurrent development and application of new algorithmic approaches for data mining, i.e., using mathematical edge detection-, thresholding- and closed-ness-based techniques that utilise pixel intensity or texture together with other parameters such as size and shape, to automatically detect and identify structures and compartments of interest (Fig. 4) (16).

Fig. 5. Scientific artwork depicting the putative protein landscape in a macrophage engulfing a bacterium.This series of three watercolour paintings by David Goodsell that show a portion of each of the two cells beautifully illustrates the distribution of macromolecules in the cells and the surrounding blood serum. Small organic molecules and water, which fill the space between the macromolecules, are omitted. The colour coding is as follows: cell membranes and their associated proteins (green), cytoplasm (blue and purple), nuclear material (red and orange), blood serum proteins (yellow and brown). Some of the subcellular structures highlighted include the nuclear pore complex, bacterial flagellum and motor, ribosomes, microtubule and tubulin subunits, actin filament, antibody, nucleosome, fibrinogen, chaperonin, RNA polymerase, DNA polymerase, spectrin, transfer RNA, topoisomerase, ATP synthase, glycolytic enzymes and insulin. Reproduced from 'Macrophage and Bacterium 2,000,000X' with permission from David Goodsell, copyright 1999.



Our second major undertaking directly relevant to the Visible CellTM Project is focused on the rapid imaging and reconstruction of whole mammalian cells at ~15-20 nm resolution using ET. This is accompanied by the development of efficient yet accurate mark-up of whole cell data, such that the 3D spatial coordinates and approximate volumes and membrane surface areas of organelles can be quantified, annotated and visualised in 3D, again with a particular focus on key compartments of the insulin biosynthetic and secretory pathway. With two whole cell reconstructions of glucose-stimulated beta cells already in hand and with analysis of both almost complete, we are on track to provide quantitative 4D measurements that will show the relative expansion of the Golgi complex together with changes in the distribution, size and morphology of mitochondria in pancreatic beta cells following exposure to stimulatory concentrations of extracellular glucose. Moreover, these and sibling datasets will allow us to pilot the development of basic methods for performing rudimentary spatial analysis queries on different organelles in 3D and 4D space, and to investigate the use of different simplified representations in spatial-temporal modelling and computational simulation of mammalian cells.Over the longer term, by providing a prototype platform

for protein and organelle annotation and database integration (see also article by Teasdale and Hamilton in this Special Technical Feature), 3D visualisation and 4D animations of cells, the Visible CellTM will emerge as advanced data environment for e-research where molecular, cell, developmental and genomic data from multiple, geographically dispersed sources will be managed, integrated, navigated and explored through computational experimentation at 'pseudo' molecular resolution (Fig. 5). Sophisticated cross-disciplinary approaches such as these should eventually allow cell,

molecular and computational biologists to model and predict changes in cell structure-function relationships that accompany key changes in cellular physiology and pathology, such as the onset and progression of chronic diseases such as Type 1 diabetes and cancer.

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toward a 'visible cell'… and beyond · 2016-07-13 · from the cover: böhm et al....

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