Complementary Superresolution Visualization of Composite Plant Microtubule Organization and Dynamics
Bibliographic record
Abstract
Microtubule bundling is an essential mechanism underlying the biased organization of interphase and mitotic microtubular systems of eukaryotes in ordered arrays. Microtubule bundle formation can be exemplified in plants where the formation of parallel microtubule systems in the cell cortex or the spindle midzone is largely owing to the microtubule crosslinking activity of a family of microtubule associated proteins, designated as MAP65s. Among the nine members of this family in Arabidopsis thaliana, MAP65-1 and MAP65-2 are ubiquitous and functionally redundant. Crosslinked microtubules can form high-order arrays which are difficult to track using widefield or confocal laser scanning microscopy approaches. Here, we followed spatiotemporal patterns of MAP65-2 localization in hypocotyl cells of Arabidopsis stably expressing fluorescent protein fusions of MAP65-2 and tubulin. To circumvent imaging difficulties arising from the density of cortical microtubule bundles, we use different superresolution approaches including Airyscan confocal laser scanning microscopy (ACLSM), structured illumination microscopy (SIM), total internal reflection SIM (TIRF-SIM), and photoactivation localization microscopy (PALM). We provide insights into spatiotemporal relations between microtubules and MAP65-2 crossbridges by combining SIM and ACLSM. We obtain further details on MAP65-2 distribution by single molecule localization microscopy (SMLM) imaging of either mEos3.2-MAP65-2 stochastic photoconversion or eGFP-MAP65-2 stochastic emission fluctuations under specific illumination conditions. Time-dependent dynamics of MAP65-2 were tracked at variable time resolution using SIM, TIRF-SIM and ACLSM and post-acquisition kymograph analysis. ACLSM imaging further allowed to track end-wise dynamics of microtubules labeled with TUA6-GFP and to correlate them with concomitant fluctuations of MAP65-2 tagged with tagRFP. All different microscopy modules examined herein are accompanied by restrictions in either the spatial resolution achieved or in the frame rates of image acquisition. PALM imaging is compromised by speed of acquisition. This limitation was partially compensated by exploiting emission fluctuations of eGFP which allowed much higher photon counts at substantially smaller time series compared to mEos3.2. SIM, TIRF-SIM and ACLSM were the methods of choice to follow the dynamics of MAP65-2 in bundles of different complexity. Conclusively, the combination of different superresolution methods allowed for inferences on the distribution and dynamics of MAP65-2 within microtubule bundles of living A. thaliana cells.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".