An alternate route for cellulose microfibril biosynthesis in plants
Data files
Nov 18, 2024 version files 11.70 GB
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Annotated_micrographs_CES-deficient_P_patens.zip
8.21 GB
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Annotated_micrographs_Z_elegans.zip
3.49 GB
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README.md
3.74 KB
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Rosette_morphometric_analysis_data_3.xlsx
32.93 KB
Abstract
Like cellulose synthases (CESAs), cellulose synthase-like D (CSLD) proteins synthesize β-1,4 glucan in plants. CSLDs are important for tip growth and cytokinesis, but it was unknown whether they form membrane complexes in vivo or produce microfibrillar cellulose. We produced viable CESA-deficient mutants of the moss Physcomitrium patens and used them to investigate CSLD function in the absence of interfering CESA activity. Microscopy and spectroscopy showed that the CESA-deficient mutants synthesize cellulose microfibrils that are indistinguishable from those in vascular plants. Correspondingly, freeze-fracture electron microscopy revealed rosette-shaped particle assemblies in the plasma membrane that are indistinguishable from CESA-containing rosette cellulose synthesis complexes (CSCs). Our data show that proteins other than CESAs, most likely CSLDs, produce cellulose microfibrils in P. patens protonemal filaments. They also suggest that the specialized roles of CSLDs in cytokinesis and tip growth are based on differential expression and different interactions with microtubules and possibly Ca2+, rather than structural differences in the microfibrils they produce.
https://doi.org/10.5061/dryad.n02v6wx5j
Description of the data and file structure
The data include two .zip files containing annotated digital freeze-fracture electron micrographs from 1) protonemal filaments of CESA-deficient Physcomitrium patens and 2) differentiating tracheary elements from Zinnia elegans. Original images are typically at 80k magnification, with a few at 70k, always with a 200 nm scale bar. As described in the main text, high confidence rosette CSCs were selected for measurement through steps outlined below. Although rosette CSCs are highly distinctive, other intramembrane proteins can also cluster, making it necessary to critically select the instances for final analysis.
1) One expert drew circles with Fiji (https://fiji.sc/) around particle clusters that might be CSCs. Fiji merged circles in a few instances of closely twinned or clustered CSCs. In two cases when the same region was photographed twice, only one view was analyzed.
2) The same expert reviewed the encircled CSCs, and either: numbered them as potentially authentic and measurable; or added a ‘?’ or ‘X’ alongside, which excluded that instance from final analysis.
3) A group of 3-5 experts finally reviewed all the candidates for final analysis. If consensus support for inclusion was lacking, an ‘X’ was applied over the encircled CSC to exclude it from final analysis.
4) The CSCs within empty circles without ‘?’ or ‘X’ alongside were included in the final analysis.
The “Image Averages” are screen captures made from a 100% on-screen views of EMAN2 outputs arising from the finally accepted and analyzed rosette CSCs from both CESA-deficient P. patens and wild type Z. elegans.
In each case 1) original images and 2) 42 class averages generated by EMAN2 (https://blake.bcm.edu/emanwiki/EMAN2) external hexagonal diameters were measured by hand.
Description of the data
The table includes raw measurements of rosette CSCs from the digital freeze-fracture electron micrographs from 1) protonemal filaments of CESA-deficient P. patens (columns A-E) and 2) differentiating tracheary elements from Z. elegans (columns F-J). In each case the data are organized as follows:
Column 1: Identity of the micrograph that includes the image of the rosette, identified by file name and coinciding with the name stamp in the micrograph.
Column 2: Identity of the cell, and for P. patens the genetic line, that was the source of the micrograph
Column 3: Raw hand measurements of rosette CSC external hexagonal diameters from the digital freeze-fracture electron micrographs.
Column 4: Identity of 6 image average classes (each containing 6 image averages) generated by EMAN2.
Column 5: Raw hand measurements of rosette CSCs external hexagonal diameters from class averages.
Summary data at the end of columns C, E, H and J were included in Fig. 4.
Sharing/Access information
NA
Code/Software
Averaged images of particles were created from rosette micrographs (at x80k) using EMAN2, version 2.91 (https://blake.bcm.edu/emanwiki/EMAN2). A scale factor of 1.598 apix was used and image contrast was inverted upon import. The e2boxer with a boxsize of 300 pixels was used for manual particle selection. After performing CTF correction in EMAN2 and specifying a particle set, we performed Reference Free Class Averaging using e2refine2d.py, typically using six classes (ncls=6). The dataset includes a Json file containing settings used to run e2refine2d.py.
Each set of CSCs was measured by hand. The Polygon selection tool in Fiji (https://fiji.sc/) was used to anchor the outer edge of each lobe without omitting parts of lobes, resulting in a hexagon around the CSC. The included area (A) within the hexagon was used to calculate the estimated long diameter (d), assuming the geometry of a regular hexagon even when small deviations from regularity existed: d = 1.732 x (SQRT (A/2.5982)) (https://rechneronline.de/pi/hexagon.php). The same CSCs were used as input for EMAN2 (https://blake.bcm.edu/emanwiki/EMAN2.