Plant Physiology Preview. Published on May 4, 2017, as DOI:10.1104/pp.17.00343
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Running Title: Vesicle dynamics during plant cytokinesis
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Corresponding author: Dr Anja Geitmann
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[email protected]
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Present address: Department of Plant Science, McGill University, Macdonald Campus, 21111
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Lakeshore, Ste-Anne-de-Bellevue, Québec H9X 3V9, Canada
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Title:
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Vesicle dynamics during plant cell cytokinesis reveals distinct
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developmental phases
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van Oostende-Triplet Chloëa,*, Guillet Dominiqueb, Triplet Thomasc, Pandzic Elvisd,
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Wiseman Paul W.b, Geitmann Anjaa,e,#
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a
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Montréal, QC, H1X 2B2, Canada, bDepartments of Physics and Chemistry, McGill University,
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Montréal, QC, H3A 2T8, Canada, cComputer Research Institute of Montreal, 405 Avenue Ogilvy
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#101, Montréal, QC, H3N 1M3, Canada, dBiomedical Imaging Facility (BMIF), Mark Wainwright
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Analytical Centre,
Lowy Cancer Research Centre C25 University of New South Wales,
NSW,
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2052, Australia, eDepartment of Plant Science, McGill University, Ste-Anne-de-Bellevue, QC,
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H9X 3V9, Canada
Institut de Recherche en Biologie Végétale, Université de Montréal, 4101 rue Sherbrooke Est,
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*Present address: Cell Biology and Image Acquisition, Faculty of Medicine, University of Ottawa,
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RGN 3171451 Smyth Road, Ottawa, ON K1H 8M5, Canada
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#
Corresponding author: [email protected]
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One-sentence Summary
Cell plate formation in dividing plant cells follows a highly consistent pattern involving
precisely choreographed vesicle motion and functionally distinct stages.
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Contributions
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AG, PWW conceived the original research plans, AG, PWW CVOT designed the experiments;
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CVOT, DG, TT, PE performed experiments; AG, PWW CVOT, DG, TT, PE analyzed data and
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AG, PWW and CVOT wrote the paper.
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Funding
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This work was funded by a team grant from Fonds de recherche du Québec – Nature et
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technologies to AG and PW. AG and PW also acknowledge support from Natural Sciences and
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Engineering Research Council of Canada Discovery Grants.
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Abstract
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Cell division in plant cells requires the deposition of a new cell wall between the two daughter
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cells. The assembly of this plate requires coordinated movement of cargo-vesicles whose size is
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below the diffraction limited resolution of the optical microscope. We combined high spatial and
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temporal resolution confocal laser scanning microscopy with advanced image processing tools and
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fluorescence fluctuation methods and distinguished three distinct phases during cell plate
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expansion in tobacco BY-2 cells: Massive delivery of pre-existing vesicles to a disk shaped region
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at the equatorial plane precedes a primary rapid expansion phase followed by a secondary, slow
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expansion phase during which the extremity of the circular plate seeks contact with the mother
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wall and brings about the separation of the two portions of cytoplasm. Different effects of
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pharmacological inhibition emphasize the distinct nature of the assembly and expansion
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mechanisms characterizing these phases.
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Cytokinesis is a highly regulated process that separates the cytoplasm of the two daughter cells
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following the formation of two nuclei during mitosis. In both animal and plant cells this process
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entails precisely coordinated events that are mediated by cytoskeletal dynamics. However, the
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mechanism differs significantly between the wall-less cells of animals and plant cells which are
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enveloped in a polysaccharidic wall. While in animal cells the separation of the cytoplasm is
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accomplished by a constriction of the plasma membrane, in plant cells a plate is constructed
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starting in the center of the equatorial region. This newly assembled wall, the cell plate, expands
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radially and eventually connects to the existing wall to completely separate the two daughter cell
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protoplasts. The process begins after the mitotic division of the nucleus and the migration of the
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two sets of chromosomes to the opposite poles of the cell pulled by the spindle microtubules. The
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cell plate is formed from cargo-vesicles which fuse in the equatorial region to first form a tubulo-
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vesicular network that expands in diameter through further addition of vesicles. While expanding
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at the periphery, the more mature, central region of the disk starts assembling a very dense fibrous
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coat composed of matrix polysaccharides such as pectin and hemicellulose (synthesized in the
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Golgi) as well as cellulose and extensins onto the membrane and subsequently deposits callose for
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mechanical stabilization (Samuels et al., 1995; Staehelin and Hepler, 1996). Gradually, the
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meshlike tubulo-vesicular network is filled in giving rise first to a tubular network and
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subsequently to a planar fenestrated sheet (Seguí-Simarro et al., 2008). Eventually, all gaps in the
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fenestrated sheet are closed and the mature cell plate consists of two parallel plasma membranes
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sandwiching a perfectly planar polysaccharidic cell wall that fuses with the parental cell wall.
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The initiation of the cell plate and its formation necessitate the accurate targeting and regulation
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of vesicle transport to the equatorial target site to ensure correct positioning and mechanical
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functionality of both the new membrane and cell wall material. Both cargo transport towards the
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newly forming cell plate, and positioning of this structure in the 3D space of the cell are controlled
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by a cytoskeletal array known as the phragmoplast. The phragmoplast is composed of
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microtubules, actin microfilaments and the cell plate assembly matrix (CPAM). The microtubules
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enable cell-plate formation by creating a scaffold that directs cell plate-forming vesicles. Their (+)-
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ends face the cell plate and contain protein complexes that control microtubule dynamics as well as
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their interactions with the CPAM, organelles and proteins. Phragmoplast actin filaments form two
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opposing sets that are oriented parallel to the phragmoplast microtubules (Higaki et al., 2008), with
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their barbed end towards the cell plate (Zhang et al., 2009). Actin barbed ends point towards each
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other but do not interdigitate at the equatorial plate as observed in somatic cells of Arabidopsis
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(Austin et al., 2005). They are proposed to restrain the accumulation and fusion of vesicles to the
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mid-zone or initiation site (Esseling-Ozdoba et al., 2008; Higaki et al., 2008) and to guide the
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phragmoplast microtubule-binding myosin VIII, thus guiding the margin of the expanding cell
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plate towards the cortical division site (Hepler et al., 2002; Molchan et al., 2002; Van Damme et
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al., 2004; Panteris, 2008; Wu and Bezanilla, 2014). The precise role of actin in cytokinesis is
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poorly understood and controversial since latrunculin B, an inhibitor of actin polymerization, was
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observed to inhibit cell plate expansion or impede its straightening by some (Nebenführ et al.,
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2000; Higaki et al., 2008; Zhang et al., 2009; Wu and Bezanilla, 2014), but not by others (Van
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Damme et al., 2011). Additional evidence for the role of actin stems from the administration of the
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myosin ATPase inhibitor BDM (Nebenführ et al., 2000; Higaki et al., 2008; Zhang et al., 2009)
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which inhibits cell plate expansion, suggesting an important role for an actomyosin-based
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mechanism in the centrifugal expansion and the alignment of the cell plate.
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The trans-Golgi network (TGN) is considered as the cornerstone compartment through which
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either newly synthesized Golgi derived proteins and polysaccharides, or endocytosed material
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(proteins, polysaccharides and lipids) from plasma membrane and cell wall, and potentially from
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late endosomes to build the new cell plate (Chow et al., 2008; Thellmann et al., 2010; Richter et
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al., 2014; Rybak et al., 2014). 3D electron tomography has yielded exquisite ultrastructural details
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about the anatomy of the growing cell plate and the fusion of vesicles between each other and to
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the plate (Samuels et al., 1995; Austin et al., 2005). However, electron micrographs are static
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snapshots in time and cannot reveal dynamics which necessitates live cell imaging. An optical
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microscopy approach on the other hand is severely challenged by the small size of the vesicles
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which is approximately 50-80 nm (Samuels et al., 1995; Austin et al., 2005). While their size does
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not per se prevent their positional tracking via optical microscopy, the combination of their small
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dimensions, rapid movement and dense crowding around the cell plate renders tracking impossible
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with conventional microscopy methods. Approximately 95,000 vesicles fuse to initiate the
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formation of the tubulo-vesicular network in the cell plate (Seguí-Simarro and Staehelin, 2006)
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and hence novel strategies need to be employed to assess their movements. We circumvent these
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challenges by combining high spatial and temporal resolution confocal laser scanning microscopy
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with advanced fluorescence fluctuation and image analysis methods. Using a specially developed,
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automated image analysis algorithm we monitored the diameter of the cell plate over time, and
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measured the intracellular transport of vesicles using spatio-temporal image correlation
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spectroscopy (STICS) (Hebert et al., 2005). We correlate these vesicle transport data with those of
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the structural elements forming the phragmoplast - actin filaments and microtubules to reveal
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mechanistic details about the assembly process as it proceeds from the time of nuclear separation
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to the full expansion of the cell plate separating the two daughter cells.
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Results
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Cell plate formation in tobacco BY-2 cells occurs in distinct phases
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In order to characterize the dynamics of cell plate formation in dividing plant cells, we stably
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transformed tobacco Bright Yellow-2 (BY-2) cells with pKN::GFP-KN. Knolle is a syntaxin
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protein or Qa-SNARE (target-SNARE) that is specifically required for the fusion of cell plate
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vesicles (Lauber et al., 1997; Waizenegger et al., 2000). The fusion protein specifically marks the
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vesicles that are delivered to form the cell plate and was imaged in 3D over time using both point
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and line laser scanning confocal microscopy. As is the case for all GFP-based localization studies,
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some of the signal may derive from unbound protein.
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To accurately measure the diameter of the expanding cell plate using extended time lapse image
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series, we developed FluMOS (Fluorescence Morphological Operators Software), a fully
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automated image processing pipeline capable of identifying cell plates within fluorescence images
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and computing their diameter (Fig. 1a, Movie 1). Plotting cell plate diameter over time revealed
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that the expansion of this disk shaped structure occurs in three phases (Fig. 1b). First, vesicles
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accumulated and aggregated in a centrally positioned region oriented perpendicularly to the length
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axis of the cell. The diameter of this disk shaped region was typically around 5.5 µm with only
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very small variations between individual cells (5.6±0.84 µm, n=6). We refer to this as phase Initial
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Plate Assembly (IPA). Once this initial disk is assembled, it rapidly expands radially (Fig. 1c)
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during a phase we call the Primary Centrifugal Growth (PCG). This rapid phase (1.44±0.44
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µm/min) proceeded until the plate reached a diameter of approximately 15.5 µm (15.6±1.9 µm,
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n=12) within the first 10 min after the beginning of the PCG. At this point the plate margins had
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not reached any of the parental cell wall boundaries. Subsequently, radial cell plate expansion
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proceeded at a reduced rate until the circular margin started fusing with the parental plasma
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membrane. We termed this phase Secondary Centrifugal Growth (SCG). The average expansion
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rate of the plate diameter during SCG was less than a third of the rate observed during PCG (Fig.
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1c, 0.35±0.13 µm/min), with significant variability between individual cells. It is remarkable that
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although the absolute standard deviation for the expansion rate over the sampled cell population
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(n=14) was smaller for the SCG phase, its relative value was much higher (47% of the average
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expansion rate) than that of the PCG phase (34%) (Fig. 1d). The final diameter of the cell plate
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was between 20 and 35 µm, depending on the size of the mother cell. The biphasic pattern of
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centrifugal cell plate expansion was distinctly different from the dynamics of expansion that would
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be expected if the volume of delivered material was constant over time. To model this we
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simplified the geometrical growth pattern by assuming a constant rate of material supply to a
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smoothly expanding disk that is solid and has constant thickness. The increase in diameter for the
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cell plate shown in Fig. 1b can be calculated with
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where t is time in minutes and ∆a is the increase in the surface area of the plate per minute.
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Given d (1 min) = 5 µm at the beginning of PCG and d (22 min) = 22 µm at the end of SCG this
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yields ∆a = 19 µm2. Comparison between the calculated and the observed dynamics shows that the
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expansion rate during PCG is faster than the theoretical rate, whereas during SCG the plate
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expands more slowly than calculated. This suggests that the rate of material delivery changes
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during the developmental steps of cell plate formation with a higher than predicted rate during
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PCG and a lower rate during SCG. To assess whether the observed phenomena are representative
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for plant cells in general, and whether they also apply to cells in a tissue context, we analyzed time
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lapse series of Arabidopsis root cells published by others (Fig. S1). The cells of the Arabidopsis
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root system differ from BY-2 cells by the facts that they are embedded into a well organized tissue
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and that they only have few or small vacuoles. Our analyses of the published data revealed that the
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initiation of the cell plate in these cells occurs on a similarly sized disk with an average diameter of
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5.7±0.75 µm (n=9). The growth of the cell plate displays clear biphasic behavior with an average
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PCG rate of 0.87±0.26 µm/min and an average SCG rate of 0.25±0.09 µm/min (paired T-test, two-
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tailed, P =0.0001). The switch point between the two growth phases in the Arabidopsis system
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consistently occurs within the first 10 min after the beginning of the PCG, and when the cell plate
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is approximately 15 µm in diameter. This confirms that the biphasic behavior is a global
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phenomenon and not specific to cells with large vacuoles or cells growing in absence of a
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surrounding tissue.
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3D surface rendering of confocal image stacks confirms the presence of distinct phases (Fig. 1e;
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Movies 2 and 3). During IPA, vesicle accumulation onto the initial 5 µm diameter disk is dense
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and supply remained high and evenly distributed during PCG. Once the cell plate assembly entered
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SCG, the cell plate displayed an inner circle that was relatively smooth, whereas the outer margin
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showed the characteristic rough surface that represented arriving and fusing vesicles. In the
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example shown, another region of 11.5 μm diameter appeared in the center while SCG proceeded,
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separated from the margin of the rough plate by a 5 μm wide smoother region. This architecture is
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consistent with the centrifugal propagation of developmental processes that ensures the formation
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of the cell plate from the center outwards.
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Vesicle dynamics during cell plate assembly
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Given the apparent changing rates of material delivery during cell plate assembly, we wanted to
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investigate in more detail the dynamics of vesicle motion in and around the expanding plate. To
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this end we performed experiments based on fluorescence recovery after photobleaching (FRAP).
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To generate a baseline for the transport dynamics of different markers, we first assessed the
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behavior of FM4-64, a lipophilic styryl dye that associates with the plasma membrane and is
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readily endocytosed by BY-2 cells. After its incorporation, FM4-64 labels most endomembrane
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systems and eventually becomes incorporated into the growing cell plate.
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To measure the delivery rate of FM4-64 we photobleached a rectangular region of interest
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(ROI) on the plasma membrane of a BY-2 cells (Fig. S2a inset). Prior to photobleaching, the cells
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were washed to remove any unincorporated dye. Fluorescence recovery in the plasma membrane
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thus had to derive from lateral diffusion within the membrane or from delivery of new material
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from the inside of the cell. Photobleaching was adjusted to reduce fluorescence intensity in the
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ROI to 20% (Figs. S2a,b). FM4-64 label in the plasma membrane showed a high degree of
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recovery with a mobile fraction (Mf) of 82% (Fig. S2b; Movie 4), which is consistent with
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previously published values (Dhonukshe et al., 2006) and a half-time of equilibration (T1/2) of
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45.0±9.5 s SE (Fig. S2a). By contrast, the same analysis made on GFP-KN revealed a much lower
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recovery (Mf of 45%, Fig S2b, Movie 5) but with statistically indistinguishable T1/2 (46.4±8.4 s
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SE, Fig. S2a) compared to FM4-64. This means that the recovery rate of FM4-64 on the parental
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plasma membrane is twice as fast as that of GFP-KN. The observed difference in mobility suggests
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that GFP-KN fluorescence recovery on the plasma membrane is likely to result from lateral
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diffusion within the plasma membrane rather than from exocytosis. In contrast, FM4-64 is a small
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lipidic probe, that diffuses faster than the large GFP-KN protein within the bilipid layer and
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several processes are likely to contribute to its recovery in the plasma membrane after
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photobleaching, including exocytosis and membrane diffusion.
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Next, we wanted to investigate the dynamics of vesicles that are specifically targeted to the cell
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plate. To do so, we performed FRAP on BY-2 cells expressing GFP-KN at different stages of cell
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plate formation (Figs. 2a,b and Movie 6). Small rectangular ROI directly on the cell plate were
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photobleached for this purpose. The T1/2 measured during PCG was clearly shorter than during
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SCG and the Mf was higher during the early expansion. During SCG we distinguished the center
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and the margin of the cell plate and found that the Mf was higher in the growing margins (51%)
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than in the center (36%). These differences were significant (unpaired T-test, two-tailed, P <0.001)
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and are indicative of spatial and temporal differences in the rates of vesicle delivery during the
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formation of the cell plate.
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Spatio-Temporal Image Correlation Spectroscopy (STICS) maps characteristic patterns of
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vesicle motion
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The FRAP results suggest that transport of vesicles towards the expanding margin of the cell
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plate is more dynamic than in the center of the plate. Therefore, it would be interesting to map the
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spatial and temporal differences in vesicle motion during cell plate expansion. However, with a
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diameter of 50 to 80 nm, these vesicles are below the diffraction limit resolution of the optical
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microscope. Moreover, they cannot be tracked individually due to their high density near the cell
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plate. To circumvent this problem we used STICS, an imaging domain extension of fluorescence
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correlation spectroscopy (Hebert et al., 2005). To determine the reliability of this method in a
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cellular system we conducted a series of validation tests. We compared velocity values of larger
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and fast moving cellular features (e.g. Golgi bodies dynamic during pollen tube growth) with
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measurements done by conventional particle tracking methods, and we compared the speed of
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movement of cytoskeletal elements in BY-2 cells to previously published values (Figs. S3 and
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S4a). For full details about the parameters used for STICS measurements of the velocities and
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output vector maps, please refer to the methods and supplemental methods (Figs. S7-9).
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Thus convinced of the reliability of STICS in the cellular context, we analyzed FM4-64 or GFP-
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KN-labeled vesicle dynamics during cytokinesis (Fig. 3). FM4-64 is a lipophilic dye and does not
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associate with the cytosol. The similarity in labeling pattern between the two markers therefore
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suggests that GFP-KN is unlikely to be expressed ectopically in the cells (FM4-64 stained vesicles,
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Movie 7). The analyses showed that during anaphase, GFP-KN vesicles within the phragmoplast
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display low velocity magnitudes around 1-1.5 μm/min (Fig. 3b). Moreover, vesicle flow coming
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from the cytoplasm in contact with the plasma membrane was detected (Fig. 3b inset). As soon as
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cell plate formation was initiated during IPA, vesicle movement occurred with a speed of up to 6
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μm/min (Fig. 3c; Movie 8 and 9). During PCG, the velocity magnitude of KN-marked organelles
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remained high, between 3 and 4 μm/min in the vicinity of the cell plate (Fig. 3d). During SCG,
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vesicles displayed slower motion in the vicinity of the central region of the cell plate with velocity
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magnitudes of approximately 2 μm/min (Fig. 3e, f, Movie 8 and 10). The highest speeds measured
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during this phase were observed at the margin of the cell plate, where they reached 3 to 4 μm/min.
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(Fig. 3e). As a negative control we included cells treated with 2,3-butanedion monoxime (BDM), a
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non-competitive myosin ATPase inhibitor that interferes with actin-based organelle transport
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(Samaj et al., 2000; Tominaga et al., 2000; Higaki et al., 2008). In our hands, the drug (20 mM)
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completely blocked cell plate growth. STICS analysis revealed that all vesicle movement in the
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vicinity the cell plate was arrested in the presence of BDM (Fig. 3a). In agreement with this, FRAP
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analysis revealed that the mobile fraction of KN labeled structures dropped from 55% to 37.4%
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upon BDM treatment. The remaining recovery is likely to result from the lateral diffusion of GFP-
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KN from the portions of the cell plate that are outside of the bleached ROI. Such horizontal
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dynamics within the cell plate can actually be observed on the STICS vector maps (Figs. 3c-f) and
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is non-negligible with speeds of 1-1.5 µm/min. BDM also affected cytoskeletal dynamics with
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differential effects on microtubules and actin filaments whose activities play important and
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different roles for cell plate formation (Fig. 4; Supplemental Material).
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IPA relies on pre-existing vesicles whose delivery is spatially confined by actin
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During normal IPA the cell plate is consistently restricted to a disk with a diameter of 5.5 µm.
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This spatial restriction was lifted when cells were treated with inhibitors of actin polymerization or
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of the endocytic pathway. Treatment with 1.25 µM LatB for 45 min caused a complete
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depolymerization of the actin cytoskeleton as visualized in BY-2 cells expressing Lifeact-GFP
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(Fig. 4i). During the IPA stage of the LatB-treated cells an excessively large disk was initiated as
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shown in cells expressing GFP-KN (14 µm contrary to 5.5 µm). The successful initiation of IPA
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under these conditions shows that actin is not required to accomplish vesicle delivery, but it seems
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to be involved in confining the accumulation of vesicles to a smaller area. In addition, we observed
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that the diameter of the microtubule array iniating the cell plate was in fact narrower than the
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mitotic spindle Fig. S5. Clearly there was a reorganization occurring but the cell plate started to be
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built after the chromosomes moved to opposite ends of the cell (Movie 8 and Fig. S5).
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To assess whether de novo protein synthesis is required for cell plate initiation, we applied
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cycloheximide (CHX) a specific inhibitor of this process. Actively dividing cells treated with CHX
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for 30 min did not show any impairment of IPA formation and the size of the initial disk was
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identical to the control with a diameter of 5.5 µm (not shown). Taken together, proper IPA
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formation on a confined site with a diameter of 5.5 µm does not require de novo protein synthesis
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but seems to involve the actin cytoskeleton and pre-existing vesicles.
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Completion of the cell plate requires actin
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The cytoskeletal elements are essential for vesicle delivery during cell plate expansion (Samuels
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et al., 1995; Kutsuna and Hasezawa, 2002; Austin et al., 2005) and both FLuMOS and FRAP
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analyses of oryzalin treated BY-2 cells are consistent with the important role of microtubules (Fig.
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4; Supplemental Material). The role of actin is less well understood. The depolymerization of actin
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resulting from LatB treatment did not affect the rapid cell plate expansion during PCG, nor the
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transition to SCG upon reaching a diameter of 15.5 µm. However, LatB treatment lowered the
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average expansion rate during SCG from 0.35 to 0.22 μm/min. In addition, vesicle supply was only
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marginally affected, since the Mf observed during FRAP of GFP-KN labeled structures in LatB
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treated samples was only slightly reduced (Fig. 4q). However, as suggested previously (Hepler et
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al., 2002) LatB prevented the expanding cell plate from contacting the parental plasma membrane
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either by arresting its expansion prior to it reaching the final size or because the plate bent (Figs.
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4n-o). Typically, the shape of cell plates formed in the presence of LatB displayed aberrant
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morphology with irregular protrusions normal to the plane of the plate (Figs. 4i,n,o).
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Endocytic pathways are involved in the expansion of the cell plate
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The origin of the material that contributes to cell plate assembly has been subject of intense
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discussion (Dhonukshe et al., 2006; Reichardt et al., 2007; Chow et al., 2008; Lam et al., 2008;
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McMichael and Bednarek, 2013; Richter et al., 2014). It was shown that Golgi derived vesicles are
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the principal but not the only source contributing to the expanding cell plate as other compartments
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composing the endocytic pathway seem to be involved as well (Reichardt et al., 2011; Richter et
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al., 2014). Since GFP-KN labeled vesicles derive from the Golgi but not from late endosome or
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plasma membrane endocytosis, we used this marker here. To probe vesicle supply routes during
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PCG and SCG we pharmacologically targeted the different trafficking pathways during these cell
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plate expansion phases (Fig. 5). In tobacco cells, used at low concentration (50 μM), the ARF-GEF
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inhibitor BrefeldinA (BFA) blocks secretory vesicle trafficking (Grebe et al., 2003; Dhonukshe et
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al., 2006; Tse et al., 2006; Reichardt et al., 2007; Lam et al., 2009) and induces the formation of a
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hybrid ER-Golgi compartment as well as a BFA compartment consisting of a mixture of the TGN
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vesicles and endosomal vesicles. However, it does not affect the late endosomal compartment
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labeled with YFP-ARA7 (Ueda et al., 2004; Dhonukshe et al., 2006) (Fig. 5c). BFA treatment
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slowed down the PCG to an expansion rate of 0.13 μm/min (compared to 1.8 μm/min in 0.1 %
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DMSO control cells, Fig. 5g) and there was no distinct transition from PCG to SCG as the rate
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only reduced very gradually when passing the transition point at 15.5 µm. The expansion rate
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during SCG was also reduced compared to the control with 0.026 μm/min (vs. 0.453 μm/min in
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control cells, Fig. 5g). During this phase, the GFP-KN mobile fraction corresponded to
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37.8±0.02% SE (Fig. 5h), compared to 55±0.03% SE for the control. Even after 1h of treatment
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with BFA (50 μM), cell plate expansion proceeded, albeit slower, and eventually the two
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cytoplasms were completely separated.
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In order to inhibit the endocytosis pathway we used wortmannin (Wort), a phosphatidylinositol-
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3-kinase (PI-3-kinase)-inhibitor, which is known to inhibit trafficking at the level of late
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endosomes/MVB and affect partially the encocytotic recycling from the plasma membrane
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(Reichardt et al., 2007). Treatment with 11.7 μM Wort slowed down cell plate expansion after 2h.
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Treatment for 30 min with 33 μM induced the swelling of MVB (diameter of 1.3 µm versus 0.7
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µm in control cells) labeled with YFP-Ara7 (Fig. 5a-b). FRAP experiments (Fig. 5h) during the
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SCG showed a limited impact of Wort on fluorescence recovery with a Mf of 39.5±0.02% SE,
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contrary to FRAP performed during PCG, where the Mf was approximately 60% (not shown),
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similar to the control. This is in agreement with the FluMOS results (Fig. 6g) showing a PCG
329
expansion rate of 0.86 μm/min in the presence of Wort. However, the expansion rate during SCG
330
slowed down to 0.12 μm/min, much slower than the control. This suggests that the membrane
331
recycling pathway is involved in the SCG phase of cell plate formation.
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12
332
Secondary centrifugal growth and fusion require de novo protein synthesis
333
Dividing cells treated with CHX for 30 min entered PCG and cell plate expansion proceeded
334
until the diameter reached 15.5 μm. During this relatively short period of CHX treatment, the
335
mobile fraction of GFP-KN was not affected (60.7±0.05% SE, not shown) and the cell plate was
336
eventually completed and fused with the plasma membrane. However, during SCG, expansion was
337
significantly slower than in the control with 0.05 μm/min (Fig. 5g). Simultaneously, the mobile
338
fraction of GFP-KN labeled structures dropped to 36.5±0.05% SE (Fig. 5h). In samples that were
339
exposed to CHX for 1h, however, expansion of existing cell plates was arrested and new plates
340
were not initiated. This means that de novo protein synthesis is required to deliver new material to
341
the expanding cell plate. If protein synthesis is blocked for a sufficiently long period prior to the
342
onset of mitosis, this will also inhibit the formation of the preexisting vesicles that are used to
343
initiate the assembly of the cell plate.
344
345
Discussion
346
Since plant cells generally do not move relative to each other, the dividing wall built during
347
cytokinesis typically remains a shared wall between the two daughter cells. The initiation,
348
generation and position of this dividing wall is therefore important for all subsequent
349
morphogenetic processes in terms of both tissue growth and organ differentiation (Müller, 2012;
350
Rasmussen et al., 2013).
351
In the present study, we developed and used a suite of image processing tools that allowed us to
352
analyze the formation of the cell plate in real time revealing three distinct phases: IPA, PCG, and
353
SCG (Fig. 6). We defined these phases in BY-2 cells based on the lateral expansion rate of the
354
growing cell plate as determined by FluMOS, but our quantitative analyses of published data of
355
Arabidopsis root cells revealed that they are consistent with the kinetics of cells in a tissue context.
356
It is safe to hypothesize that the phases we identified coincide with those based on other cellular
357
parameters, such as actin dynamics, sensitivity to caffeine (Valster and Hepler, 1997), and
358
microtubule dynamics (Seguí-Simarro et al., 2008), although exact correlation warrants
359
experimental proof.
360
While the chromosomes migrate to the poles, the mitotic spindle reorganizes into a
361
phragmoplast array. During this initial phragmoplast stage, a CPAM region starts to form at the
362
location of the future cell plate allowing the fusion of vesicles into dumbbell structures identified
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13
363
in TEM (Seguí-Simarro et al., 2004; Seguí-Simarro et al., 2008) and presumed to be apparent in
364
fluorescence microcopy. The solid phragmoplast stage is then associated with the assembly of the
365
dumbbell structures and vesicles to initiate the formation of the cell plate. Our data show that both
366
in BY-2 cells, and Arabidopsis root cells the initiation of the formation of the plate during IPA
367
consistently occurs in a disk shaped region with an average diameter of 5.5 μm (BY-2) and 5.7 µm
368
(Arabidopsis). STICS demonstrated that during this phase, vesicle trafficking to the disk region is
369
rapid and with a speed of up to 6 μm/min. Given that this is only a local average value that
370
integrates both traffic towards and away from the cell plate, the velocity of individual vesicles
371
might be much higher. Vesicle movement from the cytoplasm in the vicinity of the plasma
372
membrane detected by STICS and pharmacological evidence suggests that during this initial stage,
373
primarily preexisting rather than newly formed vesicles are recruited mainly from Golgi/TGN
374
compartments. These vesicles are delivered by the phragmoplast, which is in its initial phase (Fig.
375
6). Actin filaments seem to play an important role in focusing the localisation of the primary
376
aggregation and vesicle fusion (Esseling-Ozdoba et al., 2008; Higaki et al., 2008; Panteris, 2008).
377
We observed that the diameter of the microtubule array forming the IPA stage cell plate was
378
somewhat narrower than the mitotic spindle, which might result from forces exerted by the actin
379
cytoskeleton, as suggested previously by Higaki and coworkers (Higaki et al., 2008).
380
Evidence for Golgi-based origin of vesicles stems from the presence of methylesterified pectins
381
(as deduced from JIM7 label (Rybak et al., 2014)) in the early stage of the cell plate. Furthermore,
382
during this early stage, cell plate formation is prevented when ER to Golgi transport is inhibited by
383
low BFA concentration (Ritzenthaler et al., 2002; Lam et al., 2009; Langhans et al., 2011) or when
384
CHX is administered prior to DNA condensation to interfere with de novo protein synthesis. When
385
CHX was applied after DNA segregation the cell plate was initiated unhindered. This means that
386
the initiation of the cell plate relies on pre-existing vesicles.
387
The initiation of the formation of cell plate corresponds to the fusion of vesicles in the CPAM
388
enriched in exocyst tethering complexes (including EXO70A1 and EXO84b (Fendrych et al.,
389
2010; Rybak et al., 2014)). It is intriguing to note that the exocyst complexes move back and forth
390
between plasma membrane and the cytoplasm (Fendrych et al., 2010; Fendrych et al., 2013). In
391
addition, FM4-64 is observed at the cell plate as early as the IPA stage and that PtdIns4P
392
(originating from both Golgi and plasma membrane) is integrated into the growing cell plate
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14
393
(Vermeer et al., 2009), with the accumulation of YFP-2x-FYVE-positive endosomes at the
394
periphery of the growing cell plate (Vermeer et al., 2006; Vermeer et al., 2009).
395
The GTPase Rab-A2/A3 proteins co-localise with KN and partially co-localize with VHA-a1,
396
another early endosomal marker, on the pathway leading to MVBs (Chow et al., 2008). The
397
vesicles that initiate the formation of the cell plate may originate from the RabA2/A3-positive
398
early endosomal/TGN compartment, a key intersection between secretion and endocytosis
399
pathways.
400
Based on recent studies (Chow et al., 2008; Richter et al., 2014) it is reasonable to assume that
401
recycled components converge into the late-secretory pathway at the TGN. This means that during
402
IPA, the components forming the cell plate will have a mosaic origin and can derive from both the
403
ER and Golgi that localize in the vicinity of the future cell plate (Nebenführ et al., 2000; Rybak et
404
al., 2014), as well as from the outer envelope of the cell (plasma membrane and parental cell wall),
405
although the respective contribution of one source may dwarf the other.
406
In Arabidopsis BFA inhibits the recycling pathway while the secretory pathway is insensitive to
407
the drug. BIG3 is a BFA-resistant ARF-GEF protein involved in vesicle trafficking between the
408
TGN and the cell plate in dividing cell (Richter et al., 2014). BFA treatment of wild-type plants,
409
does not affect the localization of KN at the cell plate, but inhibits the one of PEN1, a cycling
410
plasma membrane syntaxin that normally accumulates at the cell plate in dividing cell. In big3
411
mutants BFA-treatment result in accumulation of both KN and PEN1 in the BFA compartments,
412
inhibiting the secretory pathway as well as the endocytic pathway. The convergence of the
413
pathways of recycled and newly synthesized material at the TGN compartment forces us to draw
414
the conclusions from pharmacological inhibition cautiously. The reason is that any drug inhibiting
415
secretion or the endocytosis pathway (like BFA and wortmannin) may indirectly affect the early
416
endosomal/TGN/RABA2/3 compartments (akin to a congested roundabout), which would hamper
417
the distinction between the pathways converging at the TGN and skew their respective roles.
418
Following initiation, the cell plate expands radially in two distinct stages defined by their
419
different cell plate expansion rates, the speed and spatial distribution of vesicle delivery. While the
420
resolution of optical micrographs does not allow identifying the anatomy of the cell plate at this
421
stage, electron microscopy based studies suggest that during the PCG, corresponding to the solid
422
phragmoplast stage, the dumbbell-shape intermediates fuse to form the tubulo-vesicular network
423
(Seguí-Simarro et al., 2004; Seguí-Simarro et al., 2008). Rybak et al. (Rybak et al., 2014) recently
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15
424
proposed that TRAPPII are the main tethering complexes that drive the fusion of the TGN-derived
425
vesicles to built the expanding cell plate. The “biogenesis” stage undoubtedly correlates with the
426
intense vesicle traffic that we observe during IPA and PCG as indicated by both rapid and near-
427
complete recovery of cell plate fluorescence after photobleaching and the extremely rough cell
428
plate surface observed in 4D reconstruction series.
429
Pharmacological inhibition suggests that actin is not involved in this early rapid phase of
430
expansion, whereas microtubule depolymerization leads to a dramatic drop of vesicle supply and
431
arrest in cell plate expansion. However, the initiation of the cell plate has created a new membrane
432
compartment from where endocytotic trafficking occurs to counterbalance the excess of
433
internalized membrane. Inhibiting the BFA-dependent secretion pathway reduced the expansion
434
rates during both PCG and SCG by a factor 13.5 and 17.4, respectively, but did not completely
435
block cell plate expansion or its fusion with the parental plasma membrane. While we cannot
436
exclude that BFA may not have completely inhibited the secretion pathway, these results suggest
437
that endomembrane recycling pathways play a sustained role during cell plate expansion and most
438
importantly for ensuring a rapid primary growth of the cell plate.
439
Contrary to other models which posit a gradual, time-dependent slowing of the expansion rate
440
(Higaki et al., 2008), we clearly observed a biphasic behavior with a marked phase transition
441
between PCG and SCG. The surface rendering of the 4D image series suggests that this change in
442
expansion rate coincides with the transitional phragmoplast phase as defined based on microtubule
443
configuration (Seguí-Simarro et al., 2008) (Figure 6 and S5). 3D electron tomography of apical
444
meristem cells of Arabidopsis observed during similar stages of development show the cell plate to
445
consist of a tubular network at this point (Samuels et al., 1995; Seguí-Simarro et al., 2004; Austin
446
et al., 2005).
447
The question is what causes the sudden slowdown of the expansion rate during transition from
448
PCG to SCG. One hypothesis could be that the slowdown is caused by a squeezing of the vacuoles
449
between the expanding cell plate and the parental wall. However, although the high abundance of
450
vacuoles in BY-2 cells is consistent with this notion, the fact that Arabidopsis meristematic root
451
cells show a similar biphasic behavior despite being much less vacuolated does not support a role
452
for vacuoles in bringing about a transition between PCG and SCG. Rather than being caused by
453
external constraints, our data suggest that the transition from PCG to SCG correlates with the cell
454
plate reaching a dimension-based switch point that is defined by its diameter which is consistently
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16
455
around 15 to 16 µm, both in BY-2 and Arabidopsis cells. When the cell plate reaches this critical
456
size a restructuration of the phragmoplast is likely to occur, combined with a reorganization of the
457
vesicle supply pathways. To determine a causal relationship between cytoskeletal reorganization
458
and drop in cell plate expansion it will therefore be important to temporally correlate these events
459
and test this correlation by controlled administration of cytoskeletal drugs occurring at precisely
460
timed moments during the process.
461
During SCG, vesicle delivery is targeted to the margin of the expanding cell plate which is
462
consistent with the phragmoplast reorganization from a solid into a ring shaped array (Samuels et
463
al., 1995; Seguí-Simarro et al., 2004; Austin et al., 2005) (Fig. 6). Surface rendering revealed two
464
concentric, ring-shaped rough regions on the surface of the cell plate towards the final stage of
465
SCG, approximately 20 min after the beginning of cell plate formation. This seems to suggest the
466
presence of two concentric regions of targeted vesicle delivery. Without simultaneous
467
ultrastructural evidence it is impossible to correlate these regions to a particular architecture of the
468
cell plate, but given the general centrifugal expansion pattern, we posit that the inner ring
469
corresponds to the front of the transition from tubular network to planar fenestrated sheet, whereas
470
the outer ring might represent the transition from tubulo-vesicular network to tubular network
471
(Seguí-Simarro et al., 2008). The rough margins seem to represent the locations of elevated vesicle
472
supply that fuel these formation steps (Austin et al., 2005).
473
Drugs targeting either de novo protein synthesis or endocytic pathways showed that both
474
pathways are involved in SCG. A short CHX treatment (30 min) did not significantly affect the
475
PCG growth rate but was sufficient to decrease the amount of GFP-KN-labeled vesicle supply and
476
the rate of SCG cell plate expansion. After prolonged CHX treatment (>1h), the inhibition of
477
protein synthesis prevented Golgi-derived vesicles supply to the cell plate, stopping the expansion
478
of existing cell plates or impeding new plates to initiate. Wortmannin is an inhibitor of the
479
endomembrane recycling pathway and leads to the swelling of MVBs. Upon wortmannin
480
treatment, the PCG rate decreased by half without significantly reducing the GFP-KN-labeled
481
vesicle supply. However the SCG growth rate decreased by 21-fold accompanied by a significant
482
decrease of vesicle supply as shown by our FRAP experiments. Although we cannot rule out that
483
wortmannin affected the recycling pathway at the cell plate level, this highlights the importance of
484
membrane recycling in the second stage of its growth compared to the PCG stage. These
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17
485
mechanical/dynamic data are in agreement with the general idea that excess of cell plate
486
membrane is recycled from the center and redelivered to its leading edges.
487
Similar to observations made in the highly vacuolated shoot cells of Arabidopsis thaliana, some
488
cell plates in BY-2 cells expanded asymmetrically, anchoring to one flank of the cell prior to
489
continuing its expansion. This is postulated to provide stronger protection against cytoplasmic and
490
vacuole disturbances (Cutler and Ehrhardt, 2001). Unlike the very uniform expansion rate during
491
PCG, the growth rates observed during SCG vary significantly between individual cells. One of
492
the putative reasons for this heterogeneity during SCG could be the fact that in some cells, the cell
493
plate expands perfectly symmetrically to attach simultaneously to the parental plasma membrane
494
over its entire circumference, whereas in other cells the contact with the parental plasma
495
membrane is made early at one side followed by an asymmetric expansion towards the opposite
496
side. However, no such correlation between SCG growth rate and symmetric or asymmetrical
497
expansion was observed.
498
Importantly, contrary to PCG, actin filaments play a crucial role during SCG. Pharmacological
499
interference with actin functioning during this phase reduced the growth rate of the cell plate by
500
half and impeded its proper fusion with the mother plasma membrane. This is in agreement with
501
the behavior of plant cells upon administration of inhibitors of actin polymerization such as
502
bistheonellide A (Hoshino et al., 2003; Higaki et al., 2008), or ML-7 (Hepler et al., 2002). The
503
myosins VIII, ATM1 (Van Damme et al., 2004) and Myo8A (Wu and Bezanilla, 2014), and the
504
class II formin For2a (van Gisbergen et al., 2008) are localized in the forming cell plate of BY-2
505
cells, however direct evidence of the involvement of the acto-myosin system in vesicle transport
506
has been elusive. Kinetic studies on plant-derived motor proteins have revealed that myosins are
507
fast motors with a translocation velocity close to 60 µm/sec (Henn and Sadot, 2014), while
508
kinesins have a velocity around 0.2 µm/sec (Zhu and Dixit, 2011; Kong et al., 2015). The velocity
509
of the cell plate forming vesicles measured by STICS, is therefore more consistent with a kinesin-
510
based mechanism rather than myosin.
511
Taken together our results have provided a detailed time course of cell plate formation in
512
conjunction with the associated spatial and temporal pattern of vesicle supply. Intriguingly, cell
513
plate formation occurs in three distinct phases that are characterized by very different dynamics of
514
both vesicle delivery and assembly (Fig. 6). Our data refine the existing model of the cell plate
515
expansion based on the TEM (Seguí-Simarro et al., 2004) and molecular studies (Rybak et al.,
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Copyright © 2017 American Society of Plant Biologists. All rights reserved.
18
516
2014). A clear distinction of different phases is likely to ensure a combination of optimal
517
efficiency and precision of the process. While the phragmoplast enters into solid stage, it becomes
518
narrow at the site where dumbbell-shape intermediates and vesicles fuse. This vesicle
519
accumulation, defined here as IPA stage, occurs at high velocity without producing any cell plate
520
expansion. A subsequent rapid initiation and early growth phase (PCG) ensures that the process
521
advances quickly once it is initiated. During the transitional phragmoplast stage and up to the end
522
of ring stage, a slower, and actin dependent second expansion phase (SCG) serves to adjust the cell
523
plate diameter to the mother cell size and to precisely position the connection between the margins
524
of the new wall and the parental cell wall. As this position is crucial for the morphogenesis of the
525
entire tissue and organ, it is likely subject to numerous feedback mechanisms that steer the process.
526
The differences in sensitivity towards the battery of drugs we used corroborates that fundamentally
527
different processes operate during these distinct, successive phases of cell plate formation. Our
528
spatio-temporal characterization of the process will represent a benchmark that will serve to
529
characterize the many pathways that, combined, provide a sturdy and failsafe mechanism driving
530
plant cell division.
531
532
Methods
533
Transformation and culture of BY-2 cells
534
The tobacco BY-2 cell line (Nicotiana tabacum L. cv. Bright Yellow 2) was cultured in the dark
535
(25°C, 150 rpm) as described by Nagata et al. (Samuels et al., 1995; Thiele et al., 2008). Cells
536
were subcultured weekly by transferring 1 mL of a 7-day-old culture into 50 mL of fresh BY-2
537
medium (Murashige and Skoog medium, pH=5, enriched with 0.2 g.L–1 KH2PO4, and containing
538
30 g.L-1 sucrose, 100 mg.L–1 myo-inositol, 1 mg.L–1 thiamine hydrochloride and 0.22 mg.L–1 2,4-
539
dichlorophenoxyacetic acid as an auxin source).
540
Stable transformations of BY-2 cells were performed using Agrobacterium tumefaciens strain
541
LBA4404 following the protocol by Dhonukshe et al. (Higaki et al., 2008). Stably transformed BY-
542
2 cell lines were maintained independently by culturing them every week (0.1:4) in BY-2 medium
543
in a 6-well plate shaking (25°C, 150 rpm). All lines were selected and subcultured in BY-2 medium
544
containing carbenicillin (150 mg.L-1, to kill agrobacteria) and the appropriate antibiotic: Kanamycin
545
for pSYP111::GFP-SYP111 (Nagata et al., 1992), Hygromycin for p35S::GFP-MBD, p35S::GFP-
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19
546
lifeact (cloned for this study in pMDC32 (Curtis and Grossniklaus, 2003) using Gateway strategy)
547
and p35s::Ara7-YFP.
548
Inhibitor treatments
549
FM4-64 (Life technology, Molecular Probes) dissolved in water, was applied at a 2.5 µM final
550
concentration for 30 min to BY-2 cells. Excess dye was washed away with medium just before
551
observations. All drugs were used from DMSO-dissolved 1000x stock solutions and were applied
552
to cells at final concentrations of 50 µM BFA (Bioshop), 33 µM wortmannin (Bioshop), 50 µM
553
CHX (Gold Biotechnology), 20 mM BDM (Sigma), 10 µM oryzalin (Sigma) and 1.2 µM
554
latrunculin B (Van Gestel et al., 2002) (Enzo Life Science) for the indicated periods of time.
555
Live imaging
556
Confocal laser scanning microscopy imaging was performed with a Zeiss LSM 510
557
META/LSM 5 LIVE/Axiovert 200 M system. The microscope was fitted with a 40x\ 1.3 oil EC
558
Plan Neofluar and 63x \ 1.4 oil DIC Plan Apochromat. To observe GFP-fused proteins, we used
559
the 488 nm diode laser (100 mW) with an emission filter LP505. For FRAP analyses of GFP-KN
560
with the META mode, a specific region was bleached using 2 iterations at 70% of the diode, while
561
image acquisition required 1.9% of the laser power, which result in a decrease of 80% of the
562
fluorescence intensity. LIVE imaging was performed using 19% of the diode laser power. Images
563
were 1024x1024 pixels, with a pixel size of 0.11 µm in the META mode and 0.17 µm in the LIVE
564
mode.
565
Image analysis
566
Surface rendering and 3D reconstruction were created from Z-stacks (full stacks were acquired
567
at a z-distance of 0.3 μm and a rate of 1/25 s) with the software IMARIS 7.3 (Bitplane,
568
Switzerland (http://www.bitplane.com). For FRAP analyses, quantification of fluorescence
569
intensity in the bleached ROI was performed using AIM software (Zeiss) and data were analysed
570
in Excel. To correct for photobleaching while imaging the fluorescence recovery, a reference
571
background ROI was monitored in parallel. To obtain the final recovery curve, we first normalized
572
the ROI fluorescence curve against the background curve; and then the fluorescence curve was
573
normalized to the pre-bleach fluorescence.
574
The half time of equilibration (T1/2) of the recovery was calculated as follows:
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20
575
Eq#1: T1/2=Thalf-Tpost
576
Where Thalf corresponds to the time of half recovery and Tpost to the time of maximum
577
bleaching.
578
The mobile fraction (Mf) is defined by:
579
Eq#2: Mf= (Fend-Fpost)/ (Fpre-Fpost)
580
Where Fpre corresponds to the pre-bleach fluorescence; Fpost to the fluorescence intensity after
581
bleaching and Fend, to the recovered fluorescence intensity.
582
We used Excel (Microsoft Office) to calculate averages, standard errors and T tests (two-tailed;
583
two-sample unequal variance).
584
FluMOS
585
Time lapse series of fluorescence micrographs were processed using our in-house Fluorescent
586
Morphological Operator Software (FluMOS) that relies on the Pandore image processing library
587
(A
588
https://clouard.users.greyc.fr/Pandore). FluMOS was designed as a fully automated pipeline of
589
arithmetic, morphological and thresholding operators and is capable of recognizing the cell plate
590
and computing its length. FluMOS relies on advanced segmentation operators and a morphological
591
analysis of the characteristics of the cell plates. The principal power of this algorithm is its ability
592
to determine the diameter of the cell plate despite variations in shape and continuous bleaching of
593
the structure.
594
library
of
image
processing
operators
(Version
6.6).
GREYC
laboratory.
More specifically, the pipeline consists of four main steps (see Fig. S6):
595
1. The gray-scale image is pre-processed to enhance the brightest regions using the power
596
operator, which has the added benefit of reducing the noise in darker regions. The order of
597
the power, as well as other parameters of the pipeline, was empirically determined. Typical
598
values range between 2 and 3, with higher coefficients useful to pre-process images with
599
low contrast. The image was then normalized so that all pixel intensities were in the range
600
between 0 and 100.
601
2. The normalized image is thresholded to delete darker areas of the cell and to preserve the
602
brightest areas. The value of the threshold is automatically computed so that 5 to 10% of
603
the original image is preserved, depending on the anticipated size of the cell plate. The
604
resulting image is segmented into two classes by performing binary thresholding. The
605
threshold value depends on the order of the power: the higher the power, the lower the
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Copyright © 2017 American Society of Plant Biologists. All rights reserved.
21
606
threshold, with typical values ranging between 20 and 30. Morphological dilatation and
607
erosion with a circular structuring element was performed to smooth the binary image.
608
3. The binary image is segmented to build regions from sets of connected pixels using a
609
neighborhood connexity (also known as connectivity) of 8. The shape and area of the
610
different regions is analyzed to automatically filter out isolated blobs that do not present the
611
typical morphological characteristics of cell plates. The remaining region corresponds to
612
the cell plate and is further smoothed by calculating its convex hull.
613
4. Finally, the skeleton of the convex hull is built and short barbs are removed to reduce
614
noise. The cell plate diameter was extracted by computing the length of the corresponding
615
skeleton.
616
The output is saved in a CSV file for further analysis. The skeleton is also superimposed onto
617
the original image to facilitate quality control. Once parameters are empirically determined,
618
FluMOS is fully automated. We achieved a detection rate over 95%, thus requiring very little
619
manual curation, effectively allowing us to process high-throughput microscopy imaging data and
620
perform reliable statistical analysis of cell plate expansion over extended periods of time.
621
Spatio-Temporal Image Correlation Spectroscopy (STICS)
622
Spatio-temporal image correlation spectroscopy (STICS) is a member of a family of image
623
correlation techniques that was initially developed to measure the directed transport or flow of
624
proteins inside living cells. STICS involves calculating the complete space-time correlation
625
function of the intensity fluctuations in images of a time-series recorded using a fluorescence
626
microscope. The changes in this function directly reflect the underlying transport dynamics of the
627
fluorescently labeled macromolecules in the imaged cell. We can define a generalized spatio-
628
temporal correlation function with independent spatial-lag variables ξ and η and a temporal-lag
629
variable τ for one image-detection channel a as:
630
Eq#3:
631
where
, ,
, ,
=
=
〈
, ,
〈
, ,
, , 〉 〈
,
, ,
,
〉
〉
− 〈 〉 is the intensity fluctuation in channel a at image pixel
632
position (x,y) and time t, the angular brackets in the denominator represent spatial averaging over
633
images at time t and +
634
correlation over all pixel fluctuations in pairs of images separated by a time-lag of .
in the time series, while the numerator is an ensemble average spatial
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Copyright © 2017 American Society of Plant Biologists. All rights reserved.
22
635
636
In practice, what we calculate is the discrete approximation to the generalized spatio-temporal
correlation function:
, ,
=
∑
〈
, ,
,
,
〉
637
Eq#4:
638
where N is the total number of images in the time series or time-window of interest (TOI)
639
analyzed, the spatial lag variables ξ and η represent pixel shifts in x and y, and s is the discrete
640
integer frame-lag between pairs of images in the time series. The real discrete time-lag, Δt ≈ τ, is
641
simply the product of the integer frame lag and the sampling time per image frame: Δt =s δt (where
642
δt is the sampling time per frame). This discrete correlation function is calculated by averaging the
643
spatial cross-correlation of intensity fluctuations between all image pairs separated by a time-lag
644
Δt in a fluorescence image time series. The function
645
for channel a for all pairs of images separated within the image time series by a lag time of Δt.
〈 〉 〈 〉
represents the average correlation function
646
If there is concerted translational motion of some of the fluorescent proteins during the imaging,
647
it may be observed in the time evolution of the spatio-temporal correlation function. In the STICS
648
calculation, the correlation function is first calculated for every frame in the series, with Δt =0. For
649
every image frame, this correlation function will appear as a two-dimensional Gaussian function
650
with its peak centered at zero spatial lags variable ξ = 0 and η = 0). Similarly, the correlation
651
functions for all pairs of images separated by lag times ranging from 1 to N-1 are calculated and
652
averaged for each discrete time lag to yield a mean correlation function over the TOI. A longer
653
TOI improves temporal sampling if the flow process remains constant as more fluctuations of
654
flowing particles are sampled for a given Δt and averaged. The optimal TOI for this study was
655
determined empirically by testing TOIs of 25, 50, 75 and 100 image frames. If the spatial
656
distribution of labeled particles has changed between frames, due to the movement of particles, the
657
Gaussian peak of the correlation function will change in location and/or width. For a flowing
658
population of particles, the Gaussian function will stay constant in width but its peak position will
659
translate in space. The displacement distance and direction of this correlation peak can be tracked
660
giving the underlying flow vector (i.e. magnitude and direction) of the directed movement. In the
661
case of random diffusion of the particles, no directional flow component peak is observed in the
662
correlation function, and the correlation peak stays centered at the origin while it decays in
663
amplitude and spreads out uniformly in space as Δt increases and the particles diffuse randomly in
664
all directions. A beam radius threshold of 0.8 µm was used to set the maximum e-2 radius allowed
665
for the correlation functions. Additionally, a correlation local maxima of 0.5 was applied. This is
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23
666
the ratio of the noise correlation peak amplitudes (off center) to the amplitude of the main
667
correlation function peak from the fluorescence fluctuation signal, which ensures that the noise
668
correlation peaks are not larger than the signal correlation peak, otherwise fitting is terminated.
669
These filters are used when analyzing the shape of the correlation functions for every lag time,
670
such that tracking is terminated if the signal peak of the function cannot be reliably located or if
671
the width of the peak reaches the radius threshold. As well a maximum time lag parameter is set to
672
restrict the correlation function peak fitting and tracking to lower time lag values. For the work
673
presented here, the maximum time lag parameter was 10 for TOI 25 and 50 and 20 for TOI 75 and
674
100. Note that the fitting could be terminated before the maximum time lag value if the radius or
675
the peak signal to noise criteria were not met.
676
The presence of an immobile population of particles in the region of analysis can introduce an
677
unwanted static contribution to the correlation functions that can mask the dynamics of transport
678
we wish to measure. To overcome this, we filter the image time series prior to calculating the
679
correlation functions, such that the immobile components are removed from the raw images. This
680
is done in time frequency-space, where the lowest temporal frequency components of each pixel’s
681
intensity time trace are removed before reverting back to the time-domain as has been described in
682
detail (Hebert et al., 2005). In order to enable STICS analysis of vesicles trafficking, images were
683
recorded with the LIVE mode of the ZEISS LSM 510, every 1 s for microtubules and actin (except
684
when mentioned in Figure S4) and every 0.735 s/frame for GFP-KN labeled vesicles, with a pixel
685
size of 0.17 μm. However, the vector maps were generated by performing STICS analysis in
686
parallel on multiple smaller ROIs that were 16x16 pixels and 100 image frames in time. The vector
687
maps were spatially oversampled by shifting adjacent sub-regions by a pixel shift of 2 or 4 in the x
688
and y directions.
689
690
Computer Simulations
691
Image time series of flowing particle populations were generated via MATLAB (The Mathworks,
692
Natick, MA) following similar procedures as previously described in detail (Hebert et al. 2005).
693
We will outline the key details here for understanding results presented. Image matrices of 256 x
694
256 pixels grid size and 120 total frames were populated with point particles at random grid
695
positions with a user defined density. Pixels size was set to 0.1715 μm/pixel and sequential image
696
frame iterations were 0.735 s/frame to match experimental microscopy collection parameters.
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Copyright © 2017 American Society of Plant Biologists. All rights reserved.
24
697
Particle transport was preset by user input which was a constant velocity translation at 6 μm/min in
698
this case. Periodic boundary conditions were applied in order to ensure the constant number of
699
particles in the simulation area. The particle position matrix was mathematically convolved with a
700
2D Gaussian function of e-2 radius of 0.4 μm at each time step and the output for each convolution
701
step was an image frame for the time series. The convolution with the Gaussian function simulated
702
diffraction limited imaging and acted as the spatial correlator for the underlying particles.
703
Simulated image series were analyzed by STICS as described above with variable TOI windows
704
(see Supplementary Figure S7-8).
705
706
Acknowledgments
707
We thank Dr. Zhang and Dr. Sato for providing p35s::ARA7-YFP and pSYP111::GFP-SYP111
708
(Enami et al., 2009) (GFP-KN) plasmids respectively, Dr. Andreas Nebenführ for the G-RK
709
plasmid (Nelson et al., 2007) and Dr. Richard Cyr for GFP-MBD (from MAP4) (Granger and Cyr,
710
2000).
711
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Supplemental Data
716
Supplemental Table: References used to quantify cell plate diameter in Arabidopsis meristematic
717
root cell.
718
Supplemental Figure 1: Cell plate diameter dividing A. thaliana root meristem cell.
719
Supplemental Figure 2: FRAP analysis at the plasma membrane.
720
Supplemental Figure 3: Golgi dynamics in pollen tube processed with STICS.
721
Supplemental Figure 4: STICS analysis of the vesicle supply to allow cell plate growth.
722
Supplemental Figure 5: Microtubule array from metaphase to telophase.
723
Supplemental Figure 6: FLuMOS pipeline.
724
Supplemental Figure 7: STICS Vector Maps obtained for TOI 25, 50, and 100 frames with time
725
shift oversampling.
726
Supplemental Figure 8: STICS analysis of computer simulated image series with uniform particle
727
flow with different TOI temporal sampling and different particle densities.
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Copyright © 2017 American Society of Plant Biologists. All rights reserved.
25
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Supplemental Figure 9: Statistical testing of selected TOI sizes used in STICS measurements via
729
dispersion analysis.
730
Supplemental Movie 1: Detection of cell plate growth with FluMOS.
731
Supplemental Movie 2: GFP-KN labeled cell plate expansion used for the surface rendering.
732
Supplemental Movie 3: 4D representation of a cell plate centrifugal growth.
733
Supplemental Movie 4: FRAP on plasma membrane labeled with FM4-64.
734
Supplemental Movie 5: FRAP on pKN::GFP-KN labeled plasma membrane.
735
Supplemental Movie 6: FRAP on pKN::GFP-KN labeled cell plate.
736
Supplemental Movie 7: FM4-64 labeled cell plate-forming vesicles.
737
Supplemental Movie 8: GFP-KN labeled cell plate expansion used for the STICS analysis.
738
Supplemental Movie 9: Tracking with STICS of the motion of vesicles forming cell plate during
739
IPA and PCG.
740
Supplemental Movie 10: Tracking with STICS the motion of vesicles forming cell plate during
741
SCG.
742
743
Figures
744
745
Figure 1 | Cell plate diameter tracked using FluMOS and 3D representation. (a) Typical
746
confocal laser scanning micrographs of median optical sections of GFP-KN labeled cell plate (top
747
row) detected by FluMOS software (overlay of the red detection line, bottom row). (b) Typical cell
748
plate growth dynamics based on FluMOS analysis (dashed line, IPA: Initial Plate assembly, PCG:
749
Primary Centrifugal Growth, SCG: Secondary Centrifugal Growth) and theoretical expansion
750
assuming constant vesicle supply (solid black line). (c) Average of radial growth rate during
751
primary centrifugal growth (PCG) and secondary centrifugal growth (SCG) (±SD, n=14). (d)
752
Variability in growth rates between cells shown as ratio between standard deviation and average
753
value. (e) Surface rendering of z-stacks of a growing cell plate labeled with GFP-KN. Scale bar 10
754
µm.
755
756
Figure 2 | FRAP analysis during cell plate growth. (a) Typical FRAP curves at the extremities
757
and in the center of GFP-KN labeled cell plate during SCG. Fluorescence intensity is normalized
758
to background and pre-bleach values. (b) Average of mobile fraction after FRAP on GFP-KN
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Copyright © 2017 American Society of Plant Biologists. All rights reserved.
26
759
labeled cell plate during PCG and SCG at the extremities and in the center of the plate (± SE, n=6).
760
Scale bar 10 µm.
761
762
Figure 3 | STICS analysis of the vesicle supply to allow cell plate growth. Velocity maps of
763
GFP-KN labeled vesicles analyzed over a 75 s period (100 frames). Numbers on color lookup
764
tables are movement rates in µm/min. STICS analysis were not performed on complete images but
765
on regions of interest identified by the presence of vectors or blue dots. Look up table in a applies
766
to all figures (low magnification and insets) except for dashed inset in b. ROI (yellow square)
767
corresponds to 16 x 16 pixels (2.7 µm x 2.7 µm). Pixel shift of 2, except for b and e, where pixel
768
shift is 4. (a) Negative control in the presence of BDM. (b-f) Different stages of cell plate
769
formation. Numbers indicate time in minutes.
770
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Figure 4 | Effects of pharmacological interference with cytoskeletal dynamics on cell plate
772
formation. Cells expressing GFP-MBD (a-c), GFP-KN (d-g) or Lifeact-GFP (h-j) were treated
773
with 0.1% DMSO (control, a,d,h), 10 μM oryzalin (b,e), 2.5 µM LatB (f,i) or 20 mM BDM (c,g,j).
774
(k-m) 3D Surface rendering on GFP-KN labeled cell plate in sample treated with oryzalin. (n-o)
775
3D Surface rendering of GFP-KN labeled cell plate in sample treated with LatB. (p)
776
Representative examples of cell plate growth detected with FluMOS on GFP-KN labeled cells
777
treated with cytoskeleton inhibitors. (q) Mobile fraction during FRAP of GFP-KN on the cell plate
778
of treated cells with 0.1% DMSO, 10 µM oryzalin, 1.25 µM LatB or 20 mM BDM. Standard Error
779
significant: *, highly significant: ** according to T-test. Scale bar 10 µm.
780
781
Figure 5 | Effects of vesicle trafficking inhibitors on cell plate growth. (a-c) ARA-7
782
localization in 0.1% DMSO treated cells, a), 33 µM wortmannin (b) or 50 µM BFA (c) treated
783
cells. (d-f) GFP-KN expressing cells treated in the same conditions. (g) Cell plate growth detected
784
with FluMOS on treated GFP-KN cells: 0.1% DMSO (control), 50 µM brefeldin-A (BFA), 33 µM
785
wortmannin (wort) or 50 µM cycloheximide (CHX). (h) Average of mobile fraction after FRAP in
786
GFP-KN labeled cell plates after drug treatment. Standard Error highly significant: ** according to
787
T-test.
788
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Copyright © 2017 American Society of Plant Biologists. All rights reserved.
27
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Figure 6 | Overview of the temporal time course of cell plate formation. Vesicle dynamics
790
characterizing the three phases of the cell plate assembly and drug sensitivies studied here are
791
temporally correlated with cytoskeletal dynamics and ultrastructural stages of cell plate
792
architecture identified previously.
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Abbreviations:
960
CPAM
cell plate assembly matrix
961
BDM
2,3-butanedion monoxime
962
TGN
trans-Golgi network
963
STICS
spatio-temporal image correlation spectroscopy
964
BY-2
Bright Yellow-2
965
FluMOS
fluorescence morphological operators software
966
IPA
initial plate assembly
967
PCG
primary centrifugal growth
968
SCG
secondary centrifugal growth
969
FRAP
fluorescence recovery after photobleaching
970
ROI
region of interest
971
LatB
latrunculin B
972
CHX
cycloheximide
973
BFA
brefeldinA
Downloaded from on June 15, 2017 - Published by www.plantphysiol.org
Copyright © 2017 American Society of Plant Biologists. All rights reserved.
33
974
MVB
multi vesicular bodies
975
Wort
wortmannin
Downloaded from on June 15, 2017 - Published by www.plantphysiol.org
Copyright © 2017 American Society of Plant Biologists. All rights reserved.
34
a
0’!
8’!
18’!
e
30’!
d
0!
b 25
1’37”!
SCG!
20
Diameter(μm)
IPA!
15
6’09”!
PCG!
PCG!
10
IPA!
11’09”!
5
17.5
μm
!
0
0
4
8
1
0.5
0
16
24
20
18’15”!
d
Variability(Ra=oStdev/averagein%)
Growthrate(μm/min)
c 1.5
12
Time(min)
50
PCG
SCG
40
SCG!
23’25”!
5μ
m!
30
20
11.
5
μm
!
5μ
m!
28’32”!
10
0
PCG
SCG
41’23”!
Figure1|CellplatediametertrackedusingFluMOSand3Drepresenta9on.
(a)Typicalconfocallaserscanningmicrographsofmedianop=calsec=onsofGFP-KNlabeledcellplate
(toprow)detectedbyFluMOSsoTware(overlayofthereddetec=online,boVomrow).(b)Typicalcell
plategrowthdynamicsbasedonFluMOSanalysis(dashedline,IPA:Ini=alPlateassembly,PCG:Primary
CentrifugalGrowth,SCG:SecondaryCentrifugalGrowth)andtheore=calexpansionassumingconstant
vesicle supply (solid black line). (c) Average of radial growth rate during primary centrifugal growth
(PCG)andsecondarycentrifugalgrowth(SCG)(±SD,n=14).(d)Variabilityingrowthratesbetweencells
shown as ra=o between standard devia=on and average value. (e) Surface rendering of z-stacks of a
growingcellplatelabeledwithGFP-KN.Scalebars10µm.
a
100
80
Pre-bleach
Recovery(%)
60
40
0s
Extremity1
20
Extremity2
2
C
1
Center
0
120s
0
25
50
75
100
125
Time(sec)
p=1.62.10-5
b
100
p=1.32.10-5
p=7.10-6
80
Mobilefrac=on(%)
60
40
20
0
PCG
Center
Extremi=es
SCG
Figure2|FRAPanalysisduringcellplategrowth.(a)TypicalFRAPcurvesattheextremi=esandinthecenter
ofGFP-KNlabeledcellplateduringSCG.Fluorescenceintensityisnormalizedtobackgroundandpre-bleach
values. (b) Average of mobile frac=on aTer FRAP on GFP-KN labeled cell plate during PCG and SCG at the
extremi=esandinthecenteroftheplate(±SE,n=6).Scalebar10µm.
a!
6
4.5
3
0
1.5
Nega=vecontrol(BDM)
b!
2.4
0
0!
c!
3.5’!
d!
6’!
e!
11’!
f!
13.5’!
Figure3|STICSanalysisofthe
vesicle supply to allow cell
plategrowth.Velocitymapsof
G F P - K N l a b e l e d v e s i c l e s
analyzed over a 75 s period
(100 frames). Numbers on
c o l o r l o o k u p t a b l e s a r e
movement rates in µm/min.
STICS analysis were not
p e r f o r m e d o n c o m p l e t e
images but on regions of
interest iden=fied by the
presence of vectors or blue
dots.Lookuptableinaapplies
toallfigures(lowmagnifica=on
and insets) except for dashed
inset in b. ROI (yellow square)
corresponds to 16 x 16 pixels
(2.7µmx2.7µm).PixelshiTof
2, except for b and e, where
pixel shiT is 4. (a) Nega=ve
control in the presence of
BDM. (b-f) Different stages of
cell plate forma=on. Numbers
indicate=meinminutes.
Control!
+ 10μM Oryzalin!
a!
+ 50μM BDM!
+ 1.2μM LatB!
c!
GFP-MBD!
b!
e!
f!
g!
i!
j!
GFP-KN!
d!
Lifeact-GFP!
h!
k!
!
m
n!
o!
l!
STICS:BDMinhibitcompletelycytoskeletonandvesicledynamics
p! 35
25
Mobile fraction (%)
30
Diameter (µm)
q! 70
Control
Oryzalin
LatB
20
15
10
5
0
0
5
10
15
20
25
30
35
p=0.7
p=2.3.10-4
p=1.10-2
p=4.4.10-4
60
*
50
40
**
**
30
20
10
0
Ctrl
DMSO
Oryzalin
LatB
BDM
Time (min)
Figure 4 | Effects of pharmacological interference with cytoskeletal dynamics on
cellplateforma9on.CellsexpressingGFP-MBD(a-c),GFP-KN(d-g)orLifeact-GFP(hj)weretreatedwith0.1%DMSO(control,a,d,h),10μMoryzalin(b,e),1.25µMLatB
(f,i)or50µMBDM(c,g,j).(k-m)3DSurfacerenderingonGFP-KNlabeledcellplatein
sampletreatedwithoryzalin.(n-o)3DSurfacerenderingofGFP-KNlabeledcellplate
in sample treated with LatB. (p) Representa=ve examples of cell plate growth
detectedwithFluMOSonGFP-KNlabeledcellstreatedwithcytoskeletoninhibitors.
(q)Mobilefrac=onduringFRAPofGFP-KNonthecellplateoftreatedcellswith0.1%
DMSO,10μMoryzalin,1.25μMLatBor20mMBDM.StandardErrorsignificant:*,
highlysignificant:**accordingtoT-test.Scalebar10µm.
33μM !
wortmannin!
50μM!
BFA!
b
c
d
e
f
g
35
YFP-ARA7!
a
GFP-KN!
control!
DMSO
CHX
BFA
Wort
Length (µm)
30
25
20
15
10
5
0
0
5
10
15
h
20
25
30
35
40
Time (min)
p=3.6.10-2
Mobile fraction (%)
70
p=3.10-3
p=1.10-3
60
50
40
**
**
**
BFA
Wort
CHX
30
20
10
0
DMSO
Figure 5 | Effects of vesicle trafficking inhibitors on cell plate
growth.(a-c)ARA-7localizaKonin0.1%DMSOtreatedcells,a),33
µM wortmannin (b) or 50 µM BFA (c) treated cells. (d-f) GFP-KN
expressing cells treated in the same condiKons. (g) Cell plate
growthdetectedwithFluMOSontreatedGFP-KNcells:0.1%DMSO
(control),50µMbrefeldin-A(BFA),33µMwortmannin(wort)or50
µMcycloheximide(CHX).(h)AverageofmobilefracKona\erFRAP
inGFP-KNlabeledcellplatesa\erdrugtreatment.StandardError
highlysignificant:**accordingtoT-test.
Celldivisionstage
Phragmoplaststage
Cellplatearchitecture
(observedinTEM)
Cytokinesisstages
(Rybaketal.)
Lateanaphase
Earlytelophase
IniAals
Vesicles,Dumbbells,
CPAMiniAaAon
Solid
Dumbbelsand
vesicleassembly
IniAaAon
Cellplatedevelopmentalphase
Cellplategrowthrate:
Vesiclesupplyrate:
Tubulo-vesicular
network
Biogenesis
Midtelophase
Latetelophase
TransiAonal
Ring
Tubularnetwork
Planarfenestrated
sheet
Expansion
MaturaAon
IniHalPlate
Assembly(5.5μm)
PrimaryCentrifugal
Growth(5.5-15.5μm)
SecondaryCentrifugal
Growth(>15.5μm)
Nolateral
cellplategrowth
Fastandlinear
Fast
Fast
Slow
-
++
+++
-
+
++
+(effectonthediameter)
+++
n/a
-
+
++
+++(ifaddedbeforeanaphase)
+++
n/a
+(effectonthediameter)
-
+++(onfusionwithPM)
Slowandvariablebetweencells
DrugsensiHvity(target)
CHX(newlysyntheAzedproteins)
BFA(secretoryvesicletrafficking)
T-A23(clathrin-dpdttrafficking)
Wort(MVB-recyclingpathway)
Oryzalin(microtubules)
LatB(acAn)
-
-:nosensiAvity
+:weaksensiAvity
++:sensiAve,butnoinhibiAonofvesiclesupply
+++:completeinhibiAonofvesiclesupplyandcellplategrowth
Figure6|OverviewofthetemporalHmecourseofcellplateformaHon.Vesicledynamicscharacterizing
thethreephasesofthecellplateassemblyanddrugsensiAviesstudiedherearetemporallycorrelatedwith
cytoskeletaldynamicsandultrastructuralstagesofcellplatearchitectureidenAfiedpreviously.
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Abbreviations:
CPAM cell plate assembly matrix
BDM 2,3-butanedion monoxime
TGN trans-Golgi network
STICS spatio-temporal image correlation spectroscopy
BY-2 Bright Yellow-2
FluMOS fluorescence morphological operators software
IPA initial plate assembly
PCG primary centrifugal growth
SCG secondary centrifugal growth
FRAP fluorescence recovery after photobleaching
ROI region of interest
LatB latrunculin B
CHX cycloheximide
BFA brefeldinA
MVB multi vesicular bodies
Wort wortmannin