ADVANCES IN L IVE CELL IMAG ING IN SPACEAND T IME W ITH COMBINED GFP AND YFP :

MULT I - COLOUR ONL INE SPECTRAL UNMIX INGIN FOUR D IMENS IONS

IntroductionVisualising living cells using fluorescently-tagged proteins

has led to discoveries that have reshaped our understanding of cellular mechanics. In recent years this understanding has accelerated, with advances in confocal microscopy now allowing for two important capabilities: real time four-dimensional (4D) imaging and analysis, and the simultaneous observation of multiple, spectrally similar fluorophores. In this article we describe how these two capabilities have been combined at a temporal resolution approaching one second to provide new insights into the dynamics of intracellular membranes, using dynamic tubulovesicular carriers and Golgi membranes as an example. This technique overcomes limitations that hinder the application and interpretation of epifluorescence and single-plane confocal imaging, including spectral bleed-through and out-of-focus fluorescence, whilst providing comprehensive morphological information at the level of cell organelles. Finally, we discuss the advantages and limitations of advanced imaging techniques, giving researchers insight into new and invaluable tools for exploring the truly dynamic nature of living cells.

Cellular imaging has been revolutionised through the development and application of fluorescent protein tags such as the green fluorescent protein (GFP) from Aequorea victoria (1,2). GFP and its spectral variants have facilitated the genetic tagging and non-invasive visualisation of proteins in living cells in real time, thereby revealing the exceptionally dynamic nature of many cellular processes (1,3-5). Live cell imaging techniques were originally limited to single-plane, single-colour studies (X/Y/time). With rapidly advancing technology it is now possible to conduct three-dimensional (3D) analyses over time (X/Y/Z/time − known as 4D imaging) and to do so with multiple fluorescent populations (6). For many applications of live cell imaging, the use of multiple fluorophores is essential, either for tracking or measuring multiple fluorescently-tagged proteins at once or for tracking a single fluorescent protein relative to tagged organelles or cell structures to provide contextual information.

Protein Trafficking in Live CellsProtein and membrane trafficking is one area where

live cell fluorescence imaging is generating exciting insights and new findings that are, in some cases, rewriting the textbooks. We no longer view membrane-bound carriers in exocytic and endocytic pathways simply as the small 60-100 nm diameter spherical vesicles previously viewed by electron microscopy. Live cell imaging of carriers tagged with fluorescent cargo or with membrane-associated proteins has now revealed that carriers are often large, pleiomorphic, vesicular or tubular structures that are highly dynamic and rapid in their movements through the cell (3-5). Live cell imaging has further revealed the actual, and sometimes unexpected, routes taken by carriers in exocytic and endocytic pathways (7). Studies underpinning these findings in trafficking have relied on two fundamental, technological aspects of imaging − the ability to resolve two or more fluorophores and the ability to perform high resolution, very rapid imaging to track these highly dynamic processes. Our own studies on post-Golgi trafficking in mammalian cells have demanded the optimisation of both of these requirements (7-9). Here we discuss combined aspects of confocal microscopy that have enabled us to resolve co-expressed GFP and yellow fluorescent protein (YFP)-tagged proteins on the trans-Golgi network (TGN) and to track them by maximising the detection of low intensity, rapidly moving membranes in 4D. While this is a specialised need, the techniques we discuss herein are broadly applicable to all types and applications of live cell imaging.

Separating Fluorophore Emissions - Advantages of Spectral Unmixing for Real Time ImagingThe simultaneous imaging of multiple fluorescent

populations greatly increases the level of information that can be derived from light microscopic analysis. However, the success of such studies is highly dependent on the ability to distinguish and resolve the

Luke Hammond, Jennifer Stow* and John LockInstitute for Molecular Bioscience, University of Queensland, QLD 4072

*Corresponding author: j.stow@imb.uq.edu.au

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emission spectra of each fluorescent population. Traditional methods for visualising multiple fluorophores utilise optical, filter-based mechanisms of light segregation and necessitate the use of fluorophores with clearly distinct emission spectra (Fig. 1). Moreover, the use of narrow band-pass filters can dramatically reduce the amount of signal reaching the detector. This issue becomes exacerbated in real time imaging of live cells, where low light levels and the need for rapid acquisition already contribute to a reduced signal-to-noise ratio. Alternately, the use of less stringent optical filters results in significant levels of spectral bleed-through and so is not a solution.Attempts to address the problems of optical filtering

through the development of a wide variety of spectrally-distinct fluorophores hold promise for the future. Already the range of fluorophores available is increasing, providing new combinations for multi-colour imaging (10,11). However, even within this range, not all of the fluorophores are ideal for multi-colour work. Variable expression efficiency in mammalian cells, low emission intensities from the shorter wavelength fluorophores and the tendency for some longer wavelength fluorophores to oligomerise often limit the viable combinations of fluorophores (11). Currently, the ideal experimental

combination of fluorophores might involve the use of generally robust but spectrally overlapping probes such as GFP and YFP.The combined use of spectrally overlapping fluorophores

can now be done successfully using the new generations of off-the-shelf confocal microscopes which have been developed to separate coherent light, inherent to confocality, into its spectral components prior to detection. When used appropriately this allows for spectral profiling, and subsequently, the accurate separation of spectrally-overlapping fluorophores, a process referred to as spectral unmixing (Fig. 1). Since in this case, optical filtering is not required, the entire fluorophore emission spectrum is acquired, thus maximising signal detection, an essential capability for rapid live cell imaging. This method of signal detection differentiates fluorophores based on their spectral emission profiles (Fig. 1), thereby alleviating the problem of fluorescence bleed-through and allowing subsequent extraction of autofluorescence. The ability to spectrally unmix fluorophores also removes the experimental constraint of having to choose combinations of spectrally distinct fluorophores. Indeed, spectral unmixing really accommodates any combination of fluorophores and will be increasingly powerful as the range of available fluorophores expands.

Fig. 1. Separating fluorophore emissions.Traditional optical separation methods generally depend on the use of narrow band-pass filters to segregate fluorophore emissions before they reach a detector. Unfortunately, these filters reduce the amount of signal reaching the detector and are not always efficient at preventing spectral bleed-through of neighboring fluorophores. In contrast, spectral unmixing involves a process of spectral segregation, which divides the spectrum into a series of spectral domains before reaching an array of detectors. The full range of signal intensity is collected and each domain along the spectrum is analysed separately to detect specific emissions. Through the use of spectral profiles it is then possible to 'unmix' this spectral information into the corresponding fluorophores present in the sample.

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Entire emission spectra are acquired and digitally separated

using spectral unmixing algorithms.

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Four-Dimensional ImagingSingle plane microscopy, using either epifluorescence or

confocal methods, is limited by the lack of spatial representation of axial information. The disadvantages of standard two-dimensional, time-lapse imaging using epifluorescence microscopy relate largely to two issues, namely, the incorporation of out-of-focus fluorescence from the large depth of field and the lack of directional information relating to the axial movement of objects. Confocal imaging, and the consequent acquisition of strictly in-focus information, has the dual effect of removing out-of-focus information and reducing the total information acquired. However, even minor axial movement of objects away from the narrow focal plane results in a complete loss of information relating to that object, thus reducing the ease with which 3D environments can be interrogated via this technique. To counteract this problem, a series of serial axial sections can be acquired and used to accurately reconstruct a 3D volume. In live cells, this technique can be used to generate sequential 3D volumes, each representing a single timepoint. This is only possible if the acquisition of each complete volume is rapid relative to the speed of the cellular event under observation. This highly informative, time-resolved, 3D imaging technique is referred to as 4D imaging − imaging in space and time. Examples of 4D imaging are increasingly appearing in the literature, utilising either confocal acquistion (6) or epifluorescence acquisition followed by digital deconvolution (12). In live cell imaging, it is also increasingly necessary to reconstruct 4D information for multiple co-expressed fluorophore-labeled proteins. Such information can distinguish the true degree of overlap between proteins that are seemingly colocalised in a cell compartment (as in the example below). A further advance then, on current confocal 4D imaging using multiple fluorophores, is the ability to combine rapid 4D imaging with online spectral unmixing − nominally as a fifth dimension!

High-Speed Online Unmixing in Four Dimensions - Real Life in Space, Time and Multi-colour

We have developed a method that allows for 4D imaging at a temporal resolution approaching one second whilst simultaneously incorporating online spectral unmixing (currently using a Zeiss LSM 510 META confocal microscope). This technique allows for high-speed observation of dynamic intracellular trafficking, using virtually any fluorophore combination (including GFP/YFP − see Fig. 2). To further streamline this process, we have achieved the spectral separation of fluorophores in real time, instead of using post-acquisition unmixing, which is equivalently informative but with memory requirements reduced by

up to 16-fold. Below we describe how this combination of imaging techniques, spectral unmixing and 4D imaging, was used to delineate two proteins on overlapping but distinct membrane domains of the TGN and to demonstrate that they give rise to distinct membrane tubules. The ability to resolve these proteins to this level has profound implications for our understanding of their functions in a dynamic process like membrane trafficking.

Different Membrane Domains and Carriers Labelled by YFP and GFP-Tagged GRIP GolginsThe family of golgins are large coiled-coil tethering

proteins associated with the Golgi complex and other membranes, which includes a subfamily of GRIP golgins distinguished by the presence of a common GRIP domain, a C-terminal ~45 amino acid motif that acts as a G-protein dependent membrane-recruitment domain (13,14). There are four GRIP domain golgins (p230/golgin-245, golgin-97, GCC88, GCC185) found associated with domains of the TGN and associated with various steps of post-Golgi trafficking (15). In the example provided (Fig. 2) and in a recent article (8), GFP-or YFP-tagged GRIP domains of golgin-97 and p230/golgin-245 were co-expressed with each other or with other tagged cargo proteins or Golgi markers in HeLa cells. Spectral unmixing was used in all cases to separate GFP and YFP-tagged proteins, some of which were colocalised and some were not. Four dimensional imaging further enhanced the ability to track these proteins through dynamic movements of the TGN membranes. The exact confocal acquisition parameters used in these experiments are described in Table 1 (see example 1). In Fig. 2, co-expressed GFP-golgin-97-GRIP and YFP-TNFα (tumor necrosis factor alpha) (as a cargo

parameter

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acquisition:

eg.

,

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Fig. 2. Separation of proteins at the TGN using 4D imaging and online spectral unmixing.These images depict membrane-bound carriers budding from the TGN; the relationship between a cargo protein (YFP-tagged TNFα (YFP-TNF) shown in red) and TGN-associated vesicle machinery protein (GFP-labeled golgin-97, a GRIP golgin protein shown in green) under various imaging conditions in a live HeLa cell. Spectral unmixing (top left) allows the separation of the YFP and GFP as spectrally overlapping fluorophores imaged simultaneously in real time (top left), allowing discrimination of partial overlap of the cargo and GRIP golgin on the TGN. High speed 4D confocal imaging in live cells of the YFP-TNFα cargo alone shows it budding off the TGN in discrete carriers (top right) whose rapid movement and tubular structure can here be fully resolved. By combining the 4D imaging with online spectral unmixing (top centre) it is then possible to view the relationship between cargo and TGN-associated machinery during the budding process. The lower panels represent composites of three confocal sections (0.8µm/section), captured within a 2.6 second time frame, that have been surface rendered and displayed at a 45o angle (lower panels) (from boxed area in top centre panel) and show a YFP-TNFα positive carrier (arrow) separating from the GFP-golgin97 which stays on the TGN and does not, in this instance, associate with this carrier. The technological attributes of the spectral unmixing, 4D imaging and both combined are listed. In related work we have used this technique to reveal the selective association of different golgins with carriers emerging from the TGN bearing different cargo (8) as summarised in this diagram.Scale bars: top right, top left and lower panels, 2µm; top centre panel, 5µm.

fluorescence

Spectral bleed-through possible using traditional optical separation

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protein) are clearly distinguished by spectral unmixing, showing that they are on largely separate domains of the TGN, a finding that is enhanced by viewing 4D images. Moreover, when membrane tubules emerge from the TGN, captured in 4D with spectral unmixing, it can be seen that the tubules contain the YFP-TNFα cargo but not, in this case, GFP-golgin-97-GRIP. Fig. 2 further shows the information acquired separately by spectral unmixing and 4D imaging, and demonstrates the final product as the combination of the two techniques.

In this example, spectral unmixing allowed the informative co-imaging of these GFP- and YFP-tagged fusion proteins, which, in this instance, represented a readily available combination of tagged cDNAs and ones that could be co-expressed efficiently and at appropriate levels in cells. At the same time, 4D imaging allowed temporal and 3D spatial analysis of the distribution of these two proteins, revealing the important fact that these two proteins are not exactly co-localised but have a degree of separation that turns out to be critical for their roles in trafficking out of the TGN. Specifically, these combined imaging capabilities allowed us to demonstrate the selective and dynamic association of golgin-97-GRIP with E-cadherin as a cargo and of p230/golgin-245-GRIP on tubules carrying TNFα in HeLa cells (8). Live cell imaging in 4D and with online spectral unmixing revealed novel information about the separate locations and functions of these two golgins and also provided some of the first evidence for heterogeneity of carriers emerging from the TGN.This demonstration shows how two proteins on very

specific and dynamic membrane domains can be compared in space and time. We envisage the use of this technology for many other applications in live cell imaging, and for processes beyond trafficking. To exemplify how 4D imaging and spectral unmixing could be more broadly applied and to provide practical assistance with this, we have listed parameters we predict can be used for other situations with different temporal and spatial requirements. The three sets of parameters shown (Table 1) allow observation of very rapid processes (e.g. trafficking) and slower processes (e.g. cell migration, differentiation) in live cells, labelled with almost any combination of fluorophores. These examples should be seen as basic templates from which more specific settings can be generated for a variety of individual applications.

Future DirectionsWe envisage that this five-dimensional technology, with a

combination of 4D imaging and online spectral unmixing using the parameters we describe herein, can be extended to the simultaneous analysis of greater numbers of proteins labelled with different fluorophores. Spectral unmixing of four or even more fluorophores is conceivable without significant reduction in acquisition speed or resolution. Such advances will continue to generate increasingly complex and informative data from live cell imaging. In addition, parallel, multi-positional imaging within a single cell, or within a cell population, could be incorporated to

record multiple events, thereby increasing the rate at which data can be acquired, especially in the context of low temporal-resolution events.

We wish to thank Gavin Symonds (Carl Zeiss, Australia) for his assistance and advice during the preparation of this article.

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