Atkinesin-13A Modulates Cell-Wall Synthesis and Cell Expansion in Arabidopsis thaliana via the THESEUS1 Pathway

Growth of plant organs relies on cell proliferation and expansion. While an increasingly detailed picture about the control of cell proliferation is emerging, our knowledge about the control of cell expansion remains more limited. We demonstrate here that the internal-motor kinesin AtKINESIN-13A (AtKIN13A) limits cell expansion and cell size in Arabidopsis thaliana, with loss-of-function atkin13a mutants forming larger petals with larger cells. The homolog, AtKINESIN-13B, also affects cell expansion and double mutants display growth, gametophytic and early embryonic defects, indicating a redundant role of the two genes. AtKIN13A is known to depolymerize microtubules and influence Golgi motility and distribution. Consistent with this function, AtKIN13A interacts genetically with ANGUSTIFOLIA, encoding a regulator of Golgi dynamics. Reduced AtKIN13A activity alters cell wall structure as assessed by Fourier-transformed infrared-spectroscopy and triggers signalling via the THESEUS1-dependent cell-wall integrity pathway, which in turn promotes the excess cell expansion in the atkin13a mutant. Thus, our results indicate that the intracellular activity of AtKIN13A regulates cell expansion and wall architecture via THESEUS1, providing a compelling case of interplay between cell wall integrity sensing and expansion

Golgi-localized STELLO proteins regulate the assembly and trafficking of cellulose synthase complexes in Arabidopsis

As the most abundant biopolymer on Earth, cellulose is a key structural component of the plant cell wall. Cellulose is produced at the plasma membrane by cellulose synthase (CesA) complexes (CSCs), which are assembled in the endomembrane system and trafficked to the plasma membrane. While several proteins that affect CesA activity have been identified, components that regulate CSC assembly and trafficking remain unknown. Here we show that STELLO1 and 2 are Golgi-localized proteins that can interact with CesAs and control cellulose quantity. In the absence of STELLO function, the spatial distribution within the Golgi, secretion and activity of the CSCs are impaired indicating a central role of the STELLO proteins in CSC assembly. Point mutations in the predicted catalytic domains of the STELLO proteins indicate that they are glycosyltransferases facing the Golgi lumen. Hence, we have uncovered proteins that regulate CSC assembly in the plant Golgi apparatus

Golgi-localized STELLO proteins regulate the assembly and trafficking of cellulose synthase complexes in Arabidopsis.

As the most abundant biopolymer on Earth, cellulose is a key structural component of the plant cell wall. Cellulose is produced at the plasma membrane by cellulose synthase (CesA) complexes (CSCs), which are assembled in the endomembrane system and trafficked to the plasma membrane. While several proteins that affect CesA activity have been identified, components that regulate CSC assembly and trafficking remain unknown. Here we show that STELLO1 and 2 are Golgi-localized proteins that can interact with CesAs and control cellulose quantity. In the absence of STELLO function, the spatial distribution within the Golgi, secretion and activity of the CSCs are impaired indicating a central role of the STELLO proteins in CSC assembly. Point mutations in the predicted catalytic domains of the STELLO proteins indicate that they are glycosyltransferases facing the Golgi lumen. Hence, we have uncovered proteins that regulate CSC assembly in the plant Golgi apparatus.The work presented in this paper was supported by grants from the BBSRC: BB/G016240/1 BBSRC Sustainable Energy Centre Cell Wall Sugars Programme (BSBEC) and the European Community’s Seventh Framework Programme SUNLIBB (FP7/2007-2013) under the grant agreement n° 251132 to PD. The UK 850 MHz solid-state NMR Facility was funded by EPSRC and BBSRC, as well as the University of Warwick including via part funding through Birmingham Science City Advanced Materials Projects 1 and 2 supported by Advantage West Midlands (AWM) and the European Regional Development Fund (ERDF); we thank Dinu Iuga for experimental assistance, and Chris Somerville for helpful discussions and suggesting the name STELLO. The authors acknowledge LNBio and LNLS for providing X-ray beam time (proposal GAR 15208), and the Sainsbury Laboratory Cambridge University for imaging facilities. TV was supported by an EMBO long-term fellowship (ALTF 711-2012) and by postdoctoral funding from the Philomathia Foundation. HEM was supported by an EMBO Long Term Fellowship (ALTF-1246-2013) and an NSERC Postdoctoral Fellowship (PDF-454454-2014). SP and YZ were supported by the Max-Planck Gesellschaft, and SP was also supported by a R@MAP Professor position at UoM. We thank the Biological Optical Microscopy Platform (BOMP) at University of Melbourne, and Tom Simmons and Rita Marques for assistance on sugar analyses.This is the final version of the article. It first appeared from Nature Publishing Group via http://dx.doi.org/10.1038/ncomms11656

Predicting dark respiration rates of wheat leaves from hyperspectral reflectance

Greater availability of leaf dark respiration (R dark) data could facilitate breeding efforts to raise crop yield and improve global carbon cycle modelling. However, the availability of R dark data is limited because it is cumbersome, time consuming, or destructive to measure. We report a non‐destructive and high‐throughput method of estimating R dark from leaf hyperspectral reflectance data that was derived from leaf R dark measured by a destructive high‐throughput oxygen consumption technique. We generated a large dataset of leaf R dark for wheat (1380 samples) from 90 genotypes, multiple growth stages, and growth conditions to generate models for R dark. Leaf R dark (per unit leaf area, fresh mass, dry mass or nitrogen, N) varied 7‐ to 15‐fold among individual plants, whereas traits known to scale with R dark, leaf N, and leaf mass per area (LMA) only varied twofold to fivefold. Our models predicted leaf R dark, N, and LMA with r 2 values of 0.50–0.63, 0.91, and 0.75, respectively, and relative bias of 17–18% for R dark and 7–12% for N and LMA. Our results suggest that hyperspectral model prediction of wheat leaf R dark is largely independent of leaf N and LMA. Potential drivers of hyperspectral signatures of R dark are discussed

System-wide organization of actin cytoskeleton determines organelle transport in hypocotyl plant cells

In the crowded interior of a cell, diffusion alone is insufficient to master varying transport requirements for cell sustenance and growth. The dynamic actin cytoskeleton is an essential cellular component that provides transport and cytoplasmic streaming in plant cells, but little is known about its system-level organization. Here, we resolve key challenges in understanding system-level actin-based transport. We present an automated image-based, network-driven framework that accurately incorporates both actin cytoskeleton and organelle trafficking. We demonstrate that actin cytoskeleton network properties support efficient transport in both growing and elongated hypocotyl cells. We show that organelle transport can be predicted from the system-wide cellular organization of the actin cytoskeleton. Our framework can be readily applied to investigate cytoskeleton-based transport in other organisms