Microsoft Word 63770195-file00
Yüklə 1,51 Mb. Pdf görüntüsü
|
9
The most powerful measure of a microscopy platform to resolve intracellular details is the ability 196 to discriminate between very proximal structures. For this reason, it was attempted to quantify 197 the composition of cortical microtubule bundles, taking advantage of the extensive bundling 198 observed in hypocotyl epidermal cells of the mpk4 mutant. The cortical microtubule bundle 199 composition was approached in both wild type and mpk4 hypocotyl epidermal cells labeled with 200 GFP-MBD microtubule marker, by two alternative ways: intensity profiling and determination of 201 the Rayleigh criterion. 202 First, bundles were quantified by means of additive fluorescence intensity. Ideally, this means 203 that the maximum fluorescence intensity of a given bundle would increase linearly upon the 204 successive addition of microtubules. However, it might be expected that according to the 205 specifications of the microscopy used, fluorescence intensities may become saturated after a 206 certain point making it impossible to further quantify microtubule bundles. Thus the second 207 criterion in this approach of quantitation of microtubule bundles was to determine the maximum 208 number of microtubules per bundle before fluorescence intensity was saturated. 209 By means of absolute fluorescence intensity, bundles visualized by SIM (Figs. 2A to C; Fig. 210 S4A; Figs. 2J, K), were resolvable with very good linear correlation (Figs. 2B, C; n=119, 99, 33, 211 and 26 measurements for one, two, three, and four microtubules, respectively; all p values 212 comparing absolute fluorescence intensity between 1 and 2, 2 and 3, and 3 and 4 microtubules 213 were <0.001). By contrast the linear correlation between microtubule numbers and bundle 214 fluorescence intensity was inferior with WF (Figs. 2D to F; Fig. S4B; Fig. 2K) unable to 215 discriminate between 3 and 4 microtubules (Figs. 2E, F; n=119, 99, 33, and 26 measurements for 216 one, two, three, and four microtubules, respectively; p=0.158 between 3 and 4 microtubules), and 217 such correlations deteriorated even further with CLSM showing saturation after 2 microtubules 218 (Figs. 2G to I; Fig. S4C; Fig. 2L, n=119, 99, 33, and 26 measurements for one, two, three, and 219 four microtubules, respectively; p=0.057 between 2 and 3 microtubules and p=0.051 between 3 220 and 4 microtubules). Given the broad variability and the frequent saturation of fluorescence 221 intensity of microtubule bundles observed by WF and CLSM, profiles of such bundles were 222 generated only in cells that were previously observed with SIM. 223
on July 21, 2018 - Published by Downloaded from Copyright © 2014 American Society of Plant Biologists. All rights reserved.
10
In fluorescence microscopy, the application of the Rayleigh criterion deems two proximal 224 structures separable when the minimum distance between them (peak-to-peak separation) allows 225 fluorescence intensity drop of ca. 25% of the maximum intensity of either one, provided that the 226 two maximum intensities are nearly equal. In principle, at fluorescence intensity profiles of SIM 227 showing pronounced peak separation (Fig. 3A, D; Fig. S5A) proximal microtubules were 228 indiscriminable by WF (Figs. 3B, E; Fig. S5B) and CLSM (Figs. 3C, F; Fig. S5C). The 229 application of the Rayleigh criterion proved to be particularly cumbersome, especially in the case 230 of WF and CLSM as it was difficult to locate proximal microtubules with nearly equal maximum 231 fluorescence intensities. By applying the Rayleigh criterion comparatively, SIM showed the best 232 discrimination capacity being able to deem adjacent microtubules as separate ones at 131 ±8 nm 233
(mean ±SD; n=32; Figs. 3G, J, M; Fig. S5D), while this distance was 236±17 nm for WF 234 (mean
±SD; n=32; Figs. 3H, K, M; Fig. S5E) and 243±16 nm for CLSM (mean±SD; n=32; Figs. 235
3I, L, M; Fig. S5F). 236
Individual microtubule dynamics 237
Although SIM provides greatly improved resolution with respect to commonly used descriptive 238
microscopies such as CLSM and WF there are other superresolution approaches including 239
PALM/STORM and STED which can apparently resolve subcellular structures at nearly 240
molecular level. However, PALM/STORM reconstructs superresolution images from raw 241
acquisitions in a time scale of minutes (Cox and Jones, 2013). STED, although much faster, has 242
limitations to time-lapsed imaging of very small fields of view (Westphal et al., 2008), while 243
additionally being phototoxic. Thus the main challenge for SIM would be to evaluate its 244
potential for time-lapsed imaging. It is noteworthy that only few studies of this kind (Kner et al., 245
2009, Shao et al., 2011, Fiolka et al., 2012) have been published during the 14 year period from 246
first introduction of SIM (Gustaffsson, 2000). Although SIM has been previously demonstrated 247
in plants (e.g., Fitzgibbon et al., 2010, 2013; Linnik et al., 2013; Liesche et al., 2013) its capacity 248
for time-lapsed recordings necessary for quantitative dynamic plant cell studies was never shown 249
before. 250
To test the efficiency of SIM for time-lapsed imaging, acquisition settings were adjusted to 251
achieve the best possible compromise between spatial and temporal resolution for SIM resulting 252
www.plantphysiol.org on July 21, 2018 - Published by Downloaded from Copyright © 2014 American Society of Plant Biologists. All rights reserved.
Yüklə 1,51 Mb. Dostları ilə paylaş:
|