Journal of Experimental Botany, Vol. 52, No. 356, pp. 631-640,
April 2001
© 2001 Oxford University Press
Confocal imaging of metabolism in vivo: pitfalls and possibilities
Department of Plant Sciences, University of Oxford, South Parks Road, Oxford OX1 3RB, UK
Received 29 July 2000; Accepted 24 November 2000
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Abstract |
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Confocal laser scanning microscopy (CLSM) has had wide application in morphological studies and ion imaging in plants, but little impact so far on biochemical investigations. This position is likely to change as the range of fluorescent probes increases. To illustrate the type of kinetic information that can be obtained using CLSM in an intact, living system, an analysis has been made of the two-step detoxification of monochlorobimane (MCB) following conjugation to glutathione (GSH) by a glutathione S-transferase in the cytoplasm and vacuolar sequestration of the fluorescent glutathione S-bimane (GSB) by a glutathione S-conjugate (GSX) pump. Fluorescence from the cytoplasm and vacuole of individual trichoblasts and atrichoblasts was measured from time-series of (x, y) optical sections in the elongation zone of Arabidopsis root tips. Intensity changes were calibrated and converted to amounts using compartment volumes, measured by stereological techniques. The data were well described using pseudo-first-order kinetics for the conjugation reaction and either Michaelis-Menten kinetics (Model I), or, as the GSX-pump was operating close to Vmax, a pseudo-zero-order reaction (Model II), for the GSX-pump. Analysis of 15 individual cells from two roots gave [GSH]cyt in the range 1.8–4 mM. GST activity was relatively constant on a cell basis in one root, but increased markedly in the other, giving a net increase in conjugation activity as cells progressed through the elongation zone. In contrast, GSX-pump activity increased in parallel with the increase in cell size in both roots, effectively maintaining a constant transport activity per unit root length or estimated vacuole surface area.
Key words: Confocal microscopy, glutathione, glutathione S-conjugate pump, glutathione S-transferase, monochlorobimane.
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Introduction |
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TopAbstractIntroductionWhat types of probe...What spatial and temporal...Analysis of the glutathione...Summary and projectionsReferences |
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Confocal laser scanning microscopy (CLSM) can be used to collect optical sections, free from out-of-focus blur, from fluorescent probes distributed within fixed or living plant tissues (Gilroy, 1997
; Hepler and Gunning, 1998; Roos, 2000; Blancaflor and Gilroy, 2000). The increased contrast achieved in comparison to conventional wide-field fluorescence imaging, greatly improves visualization of cellular and subcellular structures in thin optical sections, furthermore, it is straightforward to obtain 3-D views of the label distribution from a stack of such sections collected with a defined focus increment. Measurements from single optical sections or 3-D volumes can also be repeated in time to visualize and subsequently quantify dynamic events non-invasively in living tissues. Most studies in living plant systems have used CLSM to obtain morphological information, notably in conjunction with specific targeting of green fluorescent protein (GFP) to organelles or cytoskeletal structures (Hepler and Gunning, 1998; Hanson and Köhler, 2001) or, to a lesser extent, to probe physiological parameters such as pH and calcium dynamics (Gilroy, 1997; Roos, 2000). In principle, CLSM should enable in vivo measurements of many other parameters of interest to biochemists and physiologists, including metabolite levels, enzyme kinetics, subcellular compartmentalization or cell–cell partitioning. For example, one goal for this type of technique would be to measure the actual enzyme activities within specific cells, to take into account all the post-translation modification, substrate and cofactor levels, rather than the amount of mRNA and protein determined by Northern and Western blotting, respectively, or RNA and protein (antibody) in situ hybridization techniques. The ability to visualize subcellular details compares favourably with other imaging techniques, such as NMR imaging, which can currently achieve in-plane resolution of the order of 50–100 µm at best (Kockenberger, 2001).
Despite the potential benefits from non-invasive confocal imaging, there have been no studies in plants, to the best of our knowledge, that have specifically used CLSM to quantify the activity of a metabolic pathway in vivo, and only a handful of papers that have imaged a metabolite, as opposed to an inorganic ion. One major reason for this lack of data is the current paucity of suitable fluorescent probes for organic compounds of interest. This position is expected to change within the next few years with the continuing development of both chemical and protein-based reporters (Haugland, 1999), currently, however, this field is at a very embryonic stage. Thus in this paper, a number of points are considered that the authors believe will be pertinent to confocal imaging of metabolism in the future and there is an illustration of the type of information that can be obtained from a combination of in vivo CLSM and modelling techniques, using GSH-dependent detoxification of a model substrate, monochlorobimane (MCB), as an example.
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What types of probe are available to image metabolism? |
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The simplest imaging approach in plant cells would be to capitalize on the numerous intrinsic auto-fluorescent compounds, such as NAD(P)H, chlorophylls, anthocyanins, flavoproteins, phenolics, and lignins, particularly if UV-excitation is available (Hutzler et al., 1998
). For example, in animal tissues the redox state of the NADH pool has been measured from auto-fluorescence of the reduced nucleotides using UV-CLSM or two-photon laser scanning microscopy (TPLSM) (Piston et al., 1995) and used to infer changes in glucose metabolism (Bennett et al., 1996). In plants, there is one report measuring changes in redox state in vivo from changes in reduced nucleotide fluorescence under hypoxia (Roberts et al., 1984). These authors used photometry rather than imaging, but in the future, redox imaging may provide a powerful adjunct to many biochemical analyses if the weak signals from reduced pyridine nucleotides can be effectively separated from the range of other UV-excitable compounds present and quantified accurately.
In the case of fluorescent products of secondary metabolism such as the anthocyanins, flavonoids, phenolics, and lignins, their tissue and cellular localization can be readily observed in vivo, however changes in their concentration occur over such relatively long time periods suggesting that kinetic analysis may only have limited use. In contrast, the most successful application of fluorescent techniques to understanding metabolism is based on analysis of rapid (ms) transients in chlorophyll fluorescence and the inferences that can be drawn on the electron flow from the reaction centres and ultimately the activity of the dark reactions (Baker et al., 2001). The amount of chlorophyll fluorescence inversely tracks both the flow of electrons from the reaction centres and the amount of non-photochemical quenching, and has been used as a powerful tool to monitor parameters, such as the photochemical yield of PSII, over a range of different spatial resolutions. Thus, imaging systems have been developed that operate at the tissue level (Genty and Meyer, 1994) down to single chloroplasts within cells in intact leaves (Oxborough and Baker, 1997). CLSM would give an additional level of spatial resolution to these studies, however, the temporal resolution required for quantitative analysis of fluorescence transients in the ms range and the reduced signal-to-noise ratio (S/N) possible with rapid scanning have so far discouraged development of quantitative confocal analysis. Nevertheless, qualitative imaging of chlorophyll autofluorescence does provide a ready marker of chloroplast morphology or disposition (Tlalka et al., 1999).
For non-fluorescent compounds, two routes are available to develop a fluorescent assay appropriate for confocal imaging and analysis. The first approach involves a probe that is itself a substrate for one of the enzymes in the pathway and exhibits a change in its fluorescent properties during the reaction. A considerable range of fluorescent substrates or compounds that release a fluorescent product is available (Haugland, 1999). So far in plants, most if not all of these compounds have been used to report the presence of a particular enzyme activity in a given compartment (Swanson et al., 1998), or used as a measure of cell viability, rather than as a route to analyse the kinetics of specific enzymes or fluxes through the pathway.
The second approach involves a probe that interacts specifically, but reversibly, with the target but does not participate in the reaction. This class of probes is typified by the ion reporters that reversibly bind to an ion of interest with a particular dissociation constant (kd) and selectivity (Roos, 2000). This type of probe can provide information on the steady-state concentration of the target, but not directly its rate of synthesis or consumption. Based on the precedents from the ion-imaging field, the most useful reversible probes, termed ratio probes, exhibit a shift in their excitation or emission spectrum between the free and bound forms. The shift in spectrum can be readily measured as a ratio between images or average intensities measured at two wavelengths, typically corresponding to the peak wavelengths for the free and bound forms (Grynkiewicz et al., 1985). The ratio provides a convenient means to correct for changes in dye concentration, pathlength, photobleaching or leakage (Bright et al., 1989). Single wavelength probes only show changes in intensity on binding with no spectral shift. In these cases, it is more difficult to separate changes in fluorescence arising from changes in target concentration versus changes in the dye concentration as both translate into a change in intensity. The number of probes for ions is increasing rapidly as it is possible to design specific binding sites to co-ordinate the metal ligands. Probes for anions have been slower to develop and there are still many anions that cannot be measured with these techniques. There are even fewer probes for organic molecules currently available. Sophisticated probes have been developed for some metabolites, such as cAMP (Adams et al., 1991, 1999). In this case, specificity for cAMP is achieved by using the cAMP binding site of the regulatory subunit of protein kinase A. Binding of cAMP triggers dissociation of the fluorescently-tagged subunits of the protein kinase A complex that can be measured as a decrease in fluorescence resonance energy transfer (FRET) between the labelled subunits. Changes in FRET between spectral variants of GFP has also been exploited to design transgenic ratio indicators for calcium (Miyawaki et al., 1997, 1999). The use of FRET promises to be an area of great potential in the development of metabolite probes by, for example, incorporating other ligand-binding sites or substrate sites (Heim and Tsien, 1996) that alter the extent of coupling between spectral variants of GFP.
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What spatial and temporal resolution can be achieved? |
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TopAbstractIntroductionWhat types of probe...What spatial and temporal...Analysis of the glutathione...Summary and projectionsReferences |
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Assuming a suitable probe is available, it is pertinent to ask what level of spatial and temporal resolution can actually be achieved in practice using CLSM in comparison to other techniques. In theory, the smallest volume that can be conveniently imaged in a confocal microscope is around 0.2x0.2x0.6 µm in x, y and z, respectively, for an oil-immersion PlanApo lens with a numerical aperture of 1.4 (Pawley, 1995
). In physiological experiments, a number of compromises are usually required to reduce phototoxicity and keep the specimen alive and functioning as close to normal as possible. This might for example include the use of a lower numerical aperture (NA) long-working distance water-immersion lens to allow deeper penetration into the tissue and reduce the mis-match in refractive index between specimen, immersion medium and coverslip, and/or reducing the level of confocality to increase the signal-to-noise (S/N) ratio primarily at the expense of optical section thickness. Averaging over several pixels or successive frames can be used to increase the S/N ratio further, but clearly at the expense of spatial and temporal resolution. For quantitative analysis, average intensities from even larger regions-of-interest (ROIs) are usually used to increase the S/N ratio further, although the initial spatial resolution is essential to ensure the correct compartments are selected. Increasing the excitation intensity to get more signal results in more photobleaching, photodamage and phototoxicity. This is not usually an option if the specimen is to remain healthy. With these caveats in mind, a typical figure for the spatial resolution achieved during ion imaging, for example, might be around 1.2x1.2x1.2 µm in (x, y and z) after a 3x3 averaging filter applied to single optical sections. This resolution is adequate to separate larger organelles such as the nucleus, vacuole and chloroplasts, but makes spatial separation of signals from cytoplasm, apoplast, mitochondria, Golgi, and ER very much more difficult if there is label or autofluorescence present in more than one compartment.
The temporal resolution that can be achieved is also variable. The scan speeds of current confocal instruments are very impressive, typically with pixel sampling in the µs range, line scans in the ms range and full framing rates in the seconds range. Specialist instruments can run at higher speeds, with framing rates between 10 and 25 Hz. In practice, there has to be a trade-off between speed, spatial resolution and S/N. In this respect plants are particularly awkward, as the exceedingly high rate of cytoplasmic streaming can limit the amount of frame averaging that is possible without getting movement artefacts. The development of scan systems that allow single-frame sampling at slower scan speeds, line averaging and/or variable frame sizes are likely to have a beneficial impact in this area. Some measurements of rapid Ca2+ dynamics in plants have used sampling in the ms range (Goddard et al., 2000), however, most time sequences are typically sampled at 1–30 s intervals. The total exposure time is limited and represents a compromise between sampling frequency and experiment duration due to problems with phototoxicity.
Although confocal imaging has the potential to pick-up fluorescence from deep within tissues, refractive index changes, light scattering and absorption all serve to degrade the focus of the excitation beam and spread the fluorescence that is emitted. Unfortunately, the resulting blurred signal is still efficiently rejected by the confocal aperture giving a quite pronounced decrease in intensity with depth into the sample. Around 50 µm appears to be a practical limit for intact, living plant specimens for CLSM. Techniques such as multi-photon microscopy (Denk et al., 1990; Piston, 1999) also provide optical sectioning, but do not require a pinhole and should give better depth penetration. To provide a quantitative estimate of the fluorescence requires a means to account for the loss of signal with depth into the specimen. One route is to use a theoretically determined function (Török et al., 1997), but it is difficult to envisage a practical way to apply this approach to biological specimens. A second approach involves determination of some form of empirical attenuation correction that partially restores the signal intensity (White et al., 1996; Fricker et al., 1997, 2000; Gray et al., 1999).
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Analysis of the glutathione-dependent xenobiotic detoxification pathway in situ |
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TopAbstractIntroductionWhat types of probe...What spatial and temporal...Analysis of the glutathione...Summary and projectionsReferences |
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The following section illustrates the type of metabolic physiology that can be undertaken using CLSM to follow the detoxification of a model xenobiotic, monochlorobimane (MCB), following conjugation of the xenobiotic to glutathione (GSH) in the cytoplasm by a glutathione S-transferase (GST) (Fig. 1
). The glutathione then acts as a molecular tag to target the conjugate to the vacuole via a glutathione S-conjugate (GSX) pump (Coleman et al., 1997a, b; May et al., 1998; Rea et al., 1998; Swanson et al., 1998). The requirement for a GST to achieve appreciable rates of conjugation in vivo confers specificity for MCB-labelling of GSH compared to other low molecular weight thiols or protein thiols (Coleman et al., 1997b; AJ Meyer and MD Fricker, unpublished results). MCB is not fluorescent until conjugation to GSH displaces the chloride leaving group and gives rise to a fluorescent glutathione S-bimane (GSB). Although the peak excitation of GSB is around 395 nm, with a broad emission around 477 nm, GSB can be imaged with excitation at 442 nm using CLSM (Fricker et al., 2000) or at 770 nm using TPLSM (Meyer and Fricker, 2000). The combination of specific labelling and high-resolution imaging enables analysis of the detoxification capacity of each individual cell in a tissue and mapping how this alters during development.
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This technique has been used to examine the pattern of GSH-dependent detoxification activity in epidermal cells at the root tip of intact Arabidopsis seedlings. Epidermal cells in Arabidopsis roots are cut off into files by divisions of initial cells adjacent to the quiescent centre and progress through well-defined stages of elongation and differentiation into trichoblasts and atrichoblasts with increasing distance from the root tip (Dolan et al., 1993
, 1994). During this developmental sequence, the lytic vacuole is formed, possibly by fusion of very small pro-vacuoles initially into a network of strands and eventually into a single large central vacuole (Jauh et al., 1999). In addition, other types of vacuole may be present in some root cells distinguished by their different complement of tonoplast intrinsic protein (TIP) isoforms, lectins and proteases (Paris et al., 1996; Jauh et al., 1999). Given the proposed importance of vacuolar sequestration of glutathionated xenobiotics in the GSH-detoxification pathway (Coleman et al., 1997a; Rea et al., 1998), it was of interest to determine how the activities of GSTs and GSX-pumps map onto the development of the vacuolar system. To address this question, the rate of GSB formation in the cytoplasm and the rate of sequestration into the vacuole for individual cells in the epidermis at varying stages of development have been measured. Experimental details of the labelling and imaging conditions are given elsewhere (Fricker et al., 2000).
The level of fluorescence initially increases in the cytoplasm of all cells in the root observed in single optical sections followed over time (Fig. 2). Some of the label is transported into the vacuole, giving an increase in vacuolar fluorescence and eventually leading to a reduction in cytoplasmic fluorescence. In general, the smallest cells with the highest cytoplasm-to-vacuole ratios showed the greatest increase in vacuolar fluorescence.
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To analyse the data, it has been assumed that the conjugation and sequestration reactions can be described as a two-step pathway (1).
 | (1) |
). To express fluorescence levels in terms of GSB concentration requires subtraction of the average background signal (Fback) and calibration against the average fluorescence of GSB standards (Fstd) imaged under the same conditions according to equations (2) and (3).
 | (2) |
 | (3) |
). Ideally, an additional correction should be included to compensate for the amount of signal attenuation with depth into the tissue (White et al., 1996). To date, an empirical correction for Arabidopsis roots imaged with a 25x0.85 NA PlanApo multi-immersion lens has been experimentally determined (Fricker et al., 2000), but only roughly estimated an 8% loss in signal for the epidermal cells using the 60x1.4 NA PlanApo oil-immersion lens in roots (Meyer and Fricker, 2000). Comparable attenuation levels in epidermal tissues of Commelina (White et al., 1996) give a 10–15% loss of signal in at the depth equivalent to the mid-plane of the cells. Thus the true values of the GSB concentrations may be up to 8–15% higher than those presented here. Although this will affect the absolute concentrations and rates in the following analysis, the trends observed between different cells will still be maintained.
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) and vacuolar fluorescence (
) are shown for trichoblast 2 in Fig. 2The change in cytoplasmic GSB concentration over time (d[GSB]cyt/dt), in units of mol l-1 time-1, will reflect the balance between the rate of conjugation and the rate of sequestration into the vacuole. In addition, as the cells under examination are still alive and elongating, cell expansion during the assay adds a volume-dependent decrease in the apparent concentration (4).
 | (4) |
 | (5) |
so the first term approximates to a first-order rate equation, with k1GST representing the first-order rate constant (6):
 | (6) |
 | (7) |
(8).
 | (8) |
 | (9) |
; Meyer and Fricker, 2000) in parallel experiments. The changes in both values with increasing cell length are shown for trichoblasts (Fig. 4A) and atrichoblasts (Fig. 4B). Quadratic regression equations were fitted to these data and used to calculate the interpolated values of Vcyt and Vvac for each of the cells in this study. Including the cytoplasm-to-vacuole volume ratio gives equation (10) for the Michaelis-Menten model of the GSX pump and equation (11) for the simplified zero-order model:
 | (10) |
 | (11) |
 | (12) |
 | (13) |
, the differential equations (7) and (10) for Model I or (8) and (11) for Model II, were solved numerically using the 4th order Runge-Kutta method (ModelMaker, Cherwell Scientific Publishing Ltd, Oxford) and optimized iteratively against the cytoplasmic and vacuolar GSB concentrations determined from equations (2) and (3) with 
[GSH]0, 
and 
as variables used in the optimization. The output from Model I and Model II are presented for two cells in Fig. 3.
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) and vacuole (
) was calculated as the sum of the cytoplasm and vacuolar components. The data were fitted with quadratic functions and the resulting equations shown for each panel were used to as an empirical model of the relationship between compartment volume and cell length. Each marker represents data from a single cell. Cells were taken from seven different roots.The activities of the GST and GSX-pump in fmol min-1 cell-1 were calculated from the optimized model according to equations (12) and (13), respectively, and data for 12 trichoblast and 4 atrichoblast cells from overlapping regions in the elongation zone of two different roots are summarised in Fig. 5
. Cytoplasmic [GSH]cyt levels varied between 1.8–4 mM (Fig. 5A), similar to previous reports (Fricker et al., 2000; Meyer and Fricker, 2000). There was little difference between the means for trichoblasts of the two roots (2.55±0.55 mM compared to 2.60±0.65 mM). The pooled mean for the atrichoblasts was higher (3.51±0.65 mM), but the sample size is currently very low as fewer entire atrichoblasts were present in each field of view. The initial GST activity, based on the product of k1GST, [GSH]cyt and Vcyt, increased on a cell basis with increasing cell size (Fig. 5B). To assess the significance of this observation for the ability of the plant to detoxify xenobiotics, the GST activity was expressed per unit length of root (Fig. 5C). There appears to be a difference in the behaviour of the two roots on this basis. In one (Fig. 5C, open symbols), the GST activity falls per unit length, in the other root (Fig. 5C, closed symbols), there is a marked increase in GST activity per unit length. This is reflected in the two cells shown in Fig. 3, which were chosen to represent a cell with a relatively low rate of conjugation versus sequestration (Fig. 3A, C) compared to a cell with a high rate of conjugation from the second root (Fig. 3B, D). Unfortunately, the spread of cell lengths in the two roots only overlaps over a limited range making it difficult to be certain these trends would be maintained over identical developmental regions of the root. In addition, with analysis of only two roots it would be premature to draw any conclusions from this difference except to point out the variability uncovered by quantitative analysis of individual specimens that would be lost in an average measurement based on conventional biochemical extraction and assay techniques.
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The apparent Vmax of the GSX-pump also increases on a cell basis with increasing cell length (Fig. 5D
), however, in this case, the activity appears to match the rate of cell elongation, when expressed per unit length of root (Fig. 5E), or against the two-thirds power of the vacuolar volume as an approximation to the tonoplast surface area (Fig. 5F).
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Summary and projections |
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TopAbstractIntroductionWhat types of probe...What spatial and temporal...Analysis of the glutathione...Summary and projectionsReferences |
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The single most important contribution that this type of analysis can make to our understanding of metabolism is a representation of enzyme activities in identifiable cell types where the environmental context such as pH, ionic strength, substrate, and co-factor concentrations closely approximate to the conditions prevailing in vivo. There are, however, a number of significant points to be considered before this can be recommended as a useful, routine approach.
- First, the number of probes that are currently available for in vivo histochemistry is very low. The majority are fluorescent substrates or products for cleavage reactions catalysed by esterases, lipases or proteases, rather than probes useful to track primary metabolic pathways.
- Second, the analysis is very time-consuming, requiring manual (and subjective) measurement of a number of different parameters, such as average intensities from selected ROIs, attenuation corrections and compartment volumes, each with its associated error. There are, as yet, very few generic or semi-automated protocols for these analyses that can be reliably transferred between different biological systems or even between different microscope configurations.
- Third, although some parameters can be considered in isolation, the most relevant ones are derived as outputs from the simulation model and therefore subject to the normal caveats associated with such modelling approaches.
- Fourth, by measuring rates in an intact system, it is very much more difficult to bring many of the relevant parameters under experimental control or to provide, for example, the necessary range of substrate concentrations to give robust estimates of the kinetic parameters of the enzymes.
-glutamylcysteine synthetase which show elevated cytoplasmic GSH levels (Noctor et al., 1996). The situation for the GSX-pump is slightly more straightforward, as measurement below its apparent Km would only require lower levels of cytoplasmic GSB that can be readily achieved by lowering the concentration of MCB used to drive the conjugation reaction. Equally, however, the substantial amount of effort required to conduct such analyses has to be carefully weighed against the additional value of the information gained within the context of the original biological question.
On the more positive side, simulation modelling offers a powerful and flexible tool to link information from different sources and produce predictive models that can be subjected to repeated testing and refinement. For example, in the case of the GSH-dependent detoxification pathway, the models developed for MCB could be broadened to encompass other xenobiotics, including herbicides, by incorporating the relative transport activity of the GSX-pump, measured in vitro for each substrate by conventional biochemical techniques (Martinoia et al., 1993; Li et al., 1995; Lu et al., 1998). The natural extrapolation of this approach would be to use the information from different experimental systems to develop physiological models, which could be mapped onto a common anatomical framework in the form of a virtual root.
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Acknowledgments |
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We would like to thank Nick Kruger and Peter Darrah for advice during this work and comments on the manuscript, and Nick White for help with the two-photon microscopy. This work was supported by INTAS and Aventis Crop Science.
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Notes |
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1 To whom correspondence should be addressed. Fax: +00 44 1865 275074. E-mail: mark.fricker{at}plants.ox.ac.ukAbbreviationsCLSM
2 Present address: Institut für Forstbotanik und Baumphysiologie, Professur für Baumphysiologie, Universität Freiburg, Georges-Köhler-Allee 53, D-79085 Freiburg, Germany.
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Abbreviations |
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CLSM, confocal laser scanning microscopy; FRET, fluorescence resonance energy transfer; GFP, green fluorescent protein; GSB, glutathione S-bimane; GSH, glutathione; GST, glutathione S-transferase; GSX, glutathione S-conjugate; MCB, monochlorobimane; NA, numerical aperture; S/N, signal-to-noise ratio; ROI, region of interest; TIP, tonoplast intrinsic protein; TPLSM, two-photon laser scanning microscopy.
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References |
|---|
|
TopAbstractIntroductionWhat types of probe...What spatial and temporal...Analysis of the glutathione...Summary and projectionsReferences |
|---|
Adams SR, Backsai BJ, Taylor SS, Tsien RY. 1999. Optical probes for cyclic AMP. In: Mason WT, ed. Fluorescent and luminescent probes for biological activity, 2nd edn. San Diego: Academic Press, 156–172.
Adams SR, Harootunian AT, Buechler YJ, Taylor SS, Tsien RY. 1991. Fluorescence ratio imaging of cyclic AMP in single cells. Nature 349, 694–697.
Baker NR, Oxborough K, Lawson T, Morison JIL. 2001. High resolution imaging of photosynthetic activities of tissues, cells and chloroplasts in leaves. Journal of Experimental Botany 52, 615–621.
Bennett BD, Jetton TL, Ying GT, Magnuson MA, Piston DW. 1996. Quantitative subcellular imaging of glucose metabolism within intact pancreatic islets. Journal of Biological Chemistry 271, 3647–3651.
Blancaflor EB, Gilroy S. 2000. Plant cell biology in the new millenium: new tools and new insights. American Journal of Botany 87, 1547–1560.
Bright GR, Fisher GW, Rogowska J, Taylor DL. 1989. Fluorescence ratio imaging microscopy. Methods of Cell Biology 30, 157–192.[Web of Science][Medline]
Coleman JOD, Blake-Kalff MMA, Davies TGE. 1997a. Detoxification of xenobiotics by plants: chemical modification and vacuolar compartmentation. Trends in Plant Science 2, 144–151.
Coleman JOD, Randall R, Blake-Kalff MMA. 1997b. Detoxification of xenobiotics in plant cells by glutathione conjugation and vacuolar compartmentation: a fluorescent assay using monochlorobimane. Plant, Cell and Environment 20, 449–460.
Denk W, Strickler J, Webb WW. 1990. Two-photon laser scanning microscopy. Science 248, 73–76.
Dolan L, Janmaat K, Willemsen V, Linstead P, Poethig S, Roberts K, Scheres B. 1993. Cellular organization of the Arabidopsis thaliana root. Development 119, 71–84.[Abstract]
Dolan L, Duckett CM, Grierson C, Linstead P, Schneider K, Lawson E, Dean C, Roberts K. 1994. Clonal relationships and cell patterning in the root epidermis of Arabidopsis. Development 120, 2465–2474.
Fricker MD, Errington RJ, Wood J, Tlalka M, May M, White NS. 1997. Quantitative confocal fluorescence measurements in living tissue. In: Van Duijn-and B, Wiltink A, eds. Signal transduction—single cell techniques. Berlin: Springer, 413–445.
Fricker MD, May M, Meyer AJ, Sheard NS, White NS. 2000. Measurement of glutathione levels in intact roots of Arabidopsis. Journal of Microscopy 198, 162–173.[Web of Science][Medline]
Genty B, Meyer S. 1994. Quantitative mapping of leaf photosynthesis using chlorophyll fluorescence imaging. Australian Journal of Plant Physiology 22, 277–284.
Gilroy S. 1997. Fluorescence microscopy of living plant cells. Annual Review of Plant Physiology and Molecular Biology 48, 165–190.[Web of Science]
Goddard H, Manison NFH, Tomos D, Brownlee C. 2000. Elemental propagation of calcium signals in response-specific patterns determined by environmental stimulus strength. Proceedings of the National Academy of Sciences, USA 97, 1932–1937.
Gray JD, Kolesik P, Hoj PB, Coombe BG. 1999. Confocal measurement of the three-dimensional size and shape of plant paranchyma cells in a developing fruit tissue. The Plant Journal 19, 229–236.[Web of Science][Medline]
Grynkiewicz G, Poenie M, Tsien RY. 1985. A new generation of calcium indicators with greatly improved fluorescent properties. Journal of Biological Chemistry 260, 3440–3450.
Hanson MR, Köhler RH. 2001. GFP imaging: methodology and application to investigate cellular compartmentation of metabolism in plants. Journal of Experimental Botany 52, 529–539.
Haugland RP. 1999. Handbook of fluorescent probes and research chemicals, 7th edn. Molecular probes. Oregon: Eugene.
Heim R, Tsien RY. 1996. Engineering green fluorescent protein for improved brightness, longer wavelengths and fluorescence resonance energy transfer. Current Biology 6, 178–182.[Web of Science][Medline]
Hepler PK, Gunning BES. 1998. Confocal fluorescence microscopy of plant cells. Protoplasma 201, 121–157.
Howard CV, Reed MG. 1998. Unbiased stereology. Three-dimensional measurements in microscopy. Oxford: Bios Scientific Publishers.
Hutzler P, Fischbach R, Heller W, Jungblut TP, Reuber S, Schmitz R, Veit M, Weissenböck G, Schnitzler J-P. 1998. Tissue localization of phenolic compounds in plants by confocal laser scanning microscopy. Journal of Experimental Botany 49, 953–965.
Jauh G-Y, Phillips TE, Rogers JC. 1999. Tonoplast intrinsic protein isoforms as markers for vacuolar functions. The Plant Cell 11, 1867–1882.
Köckenberger W. 2001. Nuclear magnetic resonance micro-imaging in the investigation of plant cell metabolism. Journal of Experimental Botany 51, 641–652.
Li Z-S, Zhao Y, Rea PA. 1995. Magnesium adenosine 5'-triphosphate energizes transport of glutathione-S-conjugates by plant vacuolar membrane vesicles. Plant Physiology 107, 1257–1268.[Abstract]
Lu YP, Li Z-S, Drodowicz YM, Hortensteiner S, Martinoia E, Rea PA. 1998. AtMRP2, an Arabidopsis ATP binding cassette transporter able to transport glutathione S-conjugates and chlorophyll catabolites: functional comparisons with AtMRP1. The Plant Cell 10, 267–282.
Martinoia E, Grill E, Tommasini R, Kreuz K, Amrhein N. 1993. ATP-dependent glutathione S-conjugate ‘export’ pump in the vacuolar membrane of plants. Nature 364, 247–249.
May MJ, Vernoux T, Leaver CJ, Van Montagu M, Inzé D. 1998. Glutathione homeostasis in plants: implications for environmental sensing and plant development. Journal of Experimental Botany 49, 649–667.
Meyer AJ, Fricker MD. 2000. Direct measurement of glutathione in epidermal cells of intact Arabidopsis roots by two-photon laser scanning microscopy. Journal of Microscopy 198, 174–181.[Web of Science][Medline]
Miyawaki A, Llopis J, Heim R, McCaffery JM, Adams JA, Ikura M, Tsien RY. 1997. Fluorescent indicators for calcium based on green fluorescent protein and calmodulin. Nature 388, 882–887.[Medline]
Miyawaki A, Griesback O, Heim R, Tsien RY. 1999. Dynamic and quantitative Ca2+ measurements using improved cameleons. Proceedings of the National Academy of Sciences, USA 96, 2135–1240.
Noctor G, Strohm M, Jouanin L, Kunert KK, Foyer CH, Rennenberg H. 1996. Synthesis of glutathione in leaves of transgenic poplar over expressing -glutamylcysteine synthetase. Plant Physiology 112, 1071–1078.[Abstract]
Oxborough K, Baker NR. 1997. An instrument capable of imaging chlorophyll a fluorescence from intact leaves at very low irradiance and at cellular and subcellular levels of organization. Plant, Cell and Environment 20, 1473–2483.
Pawley JB. 1995. Handbook of biological confocal microscopy, 2nd edn. New York: Plenum Press.
Paris N, Stanley CM, Jones RL, Rogers JC. 1996. Plant cells contain two functionally distinct vacuolar compartments. Cell 85, 563–572.[Web of Science][Medline]
Piston DW. 1999. Imaging living cells and tissues by two-photon excitation microscopy. TICB 9, 66–69.
Piston DW, Masters BR, Webb WW. 1995. Three-dimensionally resolved NAD(P)H cellular metabolic redox imaging of the in situ cornea with two-photon excitation laser scanning microscopy. Journal of Microscopy 178, 20–27.[Web of Science][Medline]
Rea PA, Li Z-S, Lu YP, Drozdowicz YM, Martinoia E. 1998. From vacuolar GS-X pumps to multispecific ABC transporters. Annual Review of Plant Physiology and Molecular Biology 49, 727–760.[Web of Science]
Roberts JKM, Callis J, Wemmer D, Walbot V, Jardetzky O. 1984. Mechanism of cytoplasmic pH regulation in hypoxic maize root tips and its role in survival under hypoxia. Proceedings of the National Academy of Sciences, USA 81, 3379–3383.
Roos W. 2000. Ion mapping in plant cells—methods and applications in signal transduction research. Planta 210, 247–370.
Swanson SJ, Bethke P, Jones RL. 1998. Barley aleurone cells contain two types of vacuoles: characterization of lytic organelles by use of fluorescent probes. The Plant Cell 10, 685–698.
Tlalka M, Runquist M, Fricker MD. 1999. Light perception and the role of the xanthophyll cycle in blue-light-dependent chloroplast movements in Lemna trisulca L. The Plant Journal 20, 447–459.[Web of Science][Medline]
Török P, Hewlett SJ, Varga P. 1997. The role of specimen-induced spherical aberration in confocal microscopy. Journal of Microscopy 188, 158–172.
White NS, Errington RJ, Fricker MD, Wood JL. 1996. Aberration control in quantitative imaging of botanical specimens by multidimensional fluorescence microscopy. Journal of Microscopy 181, 99–116.
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