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At least 289 records · Page 16

Prediction of DIII-D Pedestal Structure from Externally Controllable Parameters

The sharp increase of pressure at the edge of a high confinement mode (H-mode) plasma, the pedestal, strongly impacts overall plasma performance. Predicting the pedestal is a necessity to control and optimize tokamak operations. An experimental data-driven machine learning (ML) approach is presented that predicts the pedestal heights and widths of electron density (ne) and electron temperature (Te) profiles as well as the separatrix ne from externally controllable parameters such as the plasma shape, heating method and power, and gas puff rate and integrated gas puff. The OMFIT framework was used with DIII-D data to efficiently, robustly, and automatically build a database of pedestal parameters to train machine learning models. Database creation was enabled by the search engine tool for DIII-D data, TokSearch, which parallelizes data fetching, enabling fast searches through basic signals of thousands of DIII-D shots and selection of relevant time intervals. Principal Component Analysis (PCA) separated the database into three clusters that represent classes of plasma shapes that are regularly used in DIII-D. The most important parameters for setting the pedestal structure were plasma current (Ip), toroidal magnetic field (Bφ), neutral beam heating power (PNBI) and shaping quantities. The Deep Jointly Informed Neural Networks (DJINN) algorithm was applied to identify suitable neural network (NN) architectures that appropriately capture the features of the pedestal database. Separate NNs were implemented for each pedestal parameter, and ensembling methods were used to improve the prediction accuracy and allowed estimation of the prediction uncertainty. The pedestal predictions of the test dataset lie within the measurement uncertainties of the pedestal parameters. The NN outperformed simple Linear Regression (LR) analysis, indicating non-linear dependencies in the pedestal structure. The presented achievements illustrate a promising path for future research, using feature extraction to infer experimental trends and thereby improve pedestal models as well as deploying NN for a fast pedestal prediction in DIII-D scenario development.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Fuel recycling and impurity characteristics in long-pulse H-mode plasmas with full metal and dynamically coated walls on EAST

We report the basic behaviors of fuel recycling and impurity accumulation during >100 s long-pulse H-mode plasma under full metal wall conditions on EAST. Significant fuel recycling and impurity rising, particularly from heavy impurities, have been observed when operating with a bare metal wall or a deteriorate real-time coated wall, which severely limits the duration of H-mode discharges. To address this issue, a novel dynamic wall coating technique combining feedforward and feedback controls has been successfully developed. The feedforward control presets the Li powder injection rate based on prior experimental observations, whereas the feedback control dynamically modulates the Li injection rate in response to real-time Li-II line emission measurements. Using this approach, a 605 s H-mode plasma has been achieved with fuel recycling and impurity level maintained stable. This result extends the previous record of a 403 s long-pulse H-mode plasma Gong et al (2024 Nucl. Fusion 64 112013) by over 200 s. It demonstrates the effectiveness of the dynamic powder injection technique in controlling fuel recycling and impurities accumulation, while prolonging plasma duration. These findings offer valuable insights into potential applications of other low-Z powder, such as boron, in ITER.

fuel recycling↗

Membrane interactions of the globular domain and the hypervariable region of KRAS4b define its unique diffusion behavior

The RAS proteins are GTP-dependent switches that regulate signaling pathways and are frequently mutated in cancer. RAS proteins concentrate in the plasma membrane via lipid-tethers and hypervariable region side-chain interactions in distinct nano-domains. However, little is known about RAS membrane dynamics and the details of RAS activation of downstream signaling. Here, we characterize RAS in live human and mouse cells using single-molecule-tracking methods and estimate RAS mobility parameters. KRAS4b exhibits confined mobility with three diffusive states distinct from the other RAS isoforms (KRAS4a, NRAS, and HRAS); and although most of the amino acid differences between RAS isoforms lie within the hypervariable region, the additional confinement of KRAS4b is largely determined by the protein’s globular domain. To understand the altered mobility of an oncogenic KRAS4b, we used complementary experimental and molecular dynamics simulation approaches to reveal a detailed mechanism.

59 BASIC BIOLOGICAL SCIENCES↗

The Madison plasma dynamo experiment: A facility for studying laboratory plasma astrophysics

The Madison plasma dynamo experiment (MPDX) is a novel, versatile, basic plasma research device designed to investigate flow driven magnetohydrodynamic instabilities and other high-β phenomena with astrophysically relevant parameters. A 3 m diameter vacuum vessel is lined with 36 rings of alternately oriented 4000 G samarium cobalt magnets, which create an axisymmetric multicusp that contains ∼14 m3of nearly magnetic field free plasma that is well confined and highly ionized (>50%). At present, 8 lanthanum hexaboride (LaB6) cathodes and 10 molybdenum anodes are inserted into the vessel and biased up to 500 V, drawing 40 A each cathode, ionizing a low pressure Ar or He fill gas and heating it. Up to 100 kW of electron cyclotron heating power is planned for additional electron heating. The LaB6cathodes are positioned in the magnetized edge to drive toroidal rotation through J × B torques that propagate into the unmagnetized core plasma. Dynamo studies on MPDX require a high magnetic Reynolds number Rm > 1000, and an adjustable fluid Reynolds number 10 1). Initial results from MPDX are presented along with a 0-dimensional power and particle balance model to predict the viscosity and resistivity to achieve dynamo action.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

An examination of the metal ion content in the active sites of human endonucleases CPSF73 and INTS11

Human cleavage and polyadenylation specificity factor (CPSF)73 (also known as CPSF3) is the endoribonuclease that catalyzes the cleavage reaction for the 3'-end processing of pre-mRNAs. The active site of CPSF73 is located at the interface between a metallo-β-lactamase domain and a β-CASP domain. Two metal ions are coordinated by conserved residues, five His and two Asp, in the active site, and they are critical for the nuclease reaction. The metal ions have long been thought to be zinc ions, but their exact identity has not been examined. Here we present evidence from inductively coupled plasma mass spectrometry and X-ray diffraction analyses that a mixture of metal ions, including Fe, Zn, and Mn, is present in the active site of CPSF73. The abundance of the various metal ions is different in samples prepared from different expression hosts. Zinc is present at less than 20% abundance in a sample expressed in insect cells, but the sample is active in cleaving a pre-mRNA substrate in a reconstituted canonical 3'-end processing machinery. Zinc is present at 75% abundance in a sample expressed in human cells, which has comparable endonuclease activity. We also observe a mixture of metal ions in the active site of the CPSF73 homolog INTS11, the endonuclease for Integrator. Taken together, our results provide further insights into the role of metal ions in the activity of CPSF73 and INTS11 for RNA 3'-end processing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Prediction of DIII-D Pedestal Structure From Externally Controllable Parameters

The sharp increase of pressure at the edge of a high confinement mode (H-mode) plasma, the pedestal, strongly impacts overall plasma performance. Predicting the pedestal is a necessity to control and optimize tokamak operations. Here, an experimental data-driven machine learning (ML) approach is presented that predicts the pedestal heights and widths of electron density (n e ) and electron temperature (T e ) profiles as well as the separatrix ne from externally controllable parameters such as the plasma shape, heating method and power, and gas puff rate and integrated gas puff. The OMFIT framework was used with DIII-D data to efficiently, robustly, and automatically build a database of pedestal parameters to train machine learning models. Database creation was enabled by the search engine tool for DIII-D data, TokSearch, which parallelizes data fetching, enabling fast searches through basic signals of thousands of DIII-D shots and selection of relevant time intervals. Principal Component Analysis (PCA) separated the database into three clusters that represent classes of plasma shapes that are regularly used in DIII-D. The most important parameters for setting the pedestal structure were plasma current (I p ), toroidal magnetic field (B Φ ), neutral beam heating power (P NBI ) and shaping quantities. The Deep Jointly Informed Neural Networks (DJINN) algorithm was applied to identify suitable neural network (NN) architectures that appropriately capture the features of the pedestal database. Separate NNs were implemented for each pedestal parameter, and ensembling methods were used to improve the prediction accuracy and allowed estimation of the prediction uncertainty. The pedestal predictions of the test dataset lie within the measurement uncertainties of the pedestal parameters. The NN outperformed simple Linear Regression (LR) analysis, indicating non-linear dependencies in the pedestal structure. The presented achievements illustrate a promising path for future research, using feature extraction to infer experimental trends and thereby improve pedestal models as well as deploying NN for a fast pedestal prediction in DIII-D scenario development.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Preparations for a European R&D roadmap for an inertial fusion demo reactor

A European consortium of 15 laboratories across nine nations have worked together under the EUROFusion Enabling Research grants for the past decade with three principle objectives. These are: (a) investigating obstacles to ignition on megaJoule-class laser facilities; (b) investigating novel alternative approaches to ignition, including basic studies for fast ignition (both electron and ion-driven), auxiliary heating, shock ignition, etc.; and (c) developing technologies that will be required in the future for a fusion reactor. This paperr presents a brief overview of these activities, along with new calculations relates the concept of auxiliary heating of inertial fusion targets, and provides possible future directions of research and development for the updated European Roadmap that is due at the end of 2020. This article is part of a discussion meeting issue ‘Prospects for high gain inertial fusion energy (part 2)’.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

VPS26 Moonlights as a β-Arrestin-like Adapter for a 7-Transmembrane RGS Protein in Arabidopsis thaliana

Extracellular signals perceived by 7-transmembrane (7TM)-spanning receptors initiate desensitization that involves the removal of these receptors from the plasma membrane. Agonist binding often evokes phosphorylation in the flexible C-terminal region and/or intracellular loop 3 of many 7TM G-protein-coupled receptors in animal cells, which consequently recruits a cytoplasmic intermediate adaptor, β-arrestin, resulting in clathrin-mediated endocytosis (CME) and downstream signaling such as transcriptional changes. Some 7TM receptors undergo CME without recruiting β-arrestin, but it is not clear how. Arrestins are not encoded in the Arabidopsis thaliana genome, yet Arabidopsis cells have a well-characterized signal-induced CME of a 7TM protein, designated Regulator of G Signaling 1 (AtRGS1). Here we show that a component of the retromer complex, Vacuolar Protein Sorting-Associated 26 (VPS26), binds the phosphorylated C-terminal region of AtRGS1 as a VPS26A/B heterodimer to form a complex that is required for downstream signaling. We propose that VPS26 moonlights as an arrestin-like adaptor in the CME of AtRGS1.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Rare earth ion-adsorption clays in the presence of iron at basic pH: Adsorption mechanism and extraction method

In this work, the uptake mechanism and influence of iron (Fe) co-adsorption on the binding of rare-earth elements (REEs) on kaolinite have been investigated. REEs and varying concentrations of Fe were co-adsorbed onto kaolinite at pH 10.5. Inductively coupled plasma mass spectrometry (ICP-MS), powder X-ray diffraction (PXRD), and X-ray photoelectron spectroscopy (XPS) were used to characterize how Fe co-adsorption influenced the uptake mechanism of REEs on kaolinite. Elemental analysis by ICP-MS revealed that the REE concentrations on kaolinite were unaffected by the presence of Fe. Crystal structure of kaolinite, determined by PXRD, was not altered after REE and Fe co-adsorption. XPS suggests that the adsorbed Fe is in the form of FeOOH, while the greatly attenuated REE XPS signals upon Fe co-adsorption implies that REEs are encapsulated by Fe species. Based on these results, we conclude that FeOOH layers were formed on top of REEs on the surface of kaolinite. Synthesized REE-Fe-kaolinite samples respond poorly to ion-exchange leaching, indicating that Fe is detrimental to the REE ion-exchange efficiency. The inhibition of ion-exchange REE extraction appears to be due to the passivating FeOOH layers. In contrast to ion-exchange methods, reductive leaching was found to dissolve the FeOOH passivating layers and liberate REEs such that they became available for ion-exchange leaching.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Novel use of Direct Simulation Monte-Carlo to Model Dynamics of COVID-19 Pandemic Spread

In this report, we evaluate a novel method for modeling the spread of COVID-19 pandemic. In this new approach we leverage methods and algorithms developed for fully-kinetic plasma physics simulations using Particle-In-Cell (PIC) Direct Simulation Monte-Carlo (DSMC) models. This approach then leverages Sandia-unique simulation capabilities, and High-Performance Computer (HPC) resources and expertise in particle-particle interactions using stochastic processes. Our hypothesis is that this approach would provide a more efficient platform with assumptions based on physical data that would then enable the user to assess the impact of mitigation strategies and forecast different phases of infection. This work addresses key scientific questions related to the assumptions this new approach must make to model the interactions of people using algorithms typically used for modeling particle interactions in physics codes (kinetic plasma, gas dynamics). The model developed uses rational/physical inputs while also providing critical insight; the results could serve as inputs to, or alternatives for, existing models. The model work presented was developed over a four-week time frame, thus far showing promising results and many ways in which this model/approach could be improved. This work is aimed at providing a proof-of-concept for this new pandemic modeling approach, which could have an immediate impact on the COVID-19 pandemic modeling, while laying a basis to model future pandemic scenarios in a manner that is timely and efficient. Additionally, this new approach provides new visualization tools to help epidemiologists comprehend and articulate the spread of this and other pandemics as well as a more general tool to determine key parameters needed in order to better predict pandemic modeling in the future. In the report we describe our model for pandemic modeling, apply this model to COVID-19 data for New York City (NYC), assess model sensitivities to different inputs and parameters and , finally, propagate the model forward under different conditions to assess the effects of mitigation and associated timing. Finally, our approach will help understand the role of asymptomatic cases, and could be extended to elucidate the role of recovered individuals in the second round of the infection, which is currently being ignored.

59 BASIC BIOLOGICAL SCIENCES↗

The first DEP domain of the RhoGEF P-Rex1 autoinhibits activity and contributes to membrane binding

Phosphatidylinositol (3,4,5)-trisphosphate (PIP 3 )-dependent Rac exchanger 1 (P-Rex1) catalyzes the exchange of GDP for GTP on Rac GTPases, thereby triggering changes in the actin cytoskeleton and in transcription. Its overexpression is highly correlated with the metastasis of certain cancers. P-Rex1 recruitment to the plasma membrane and its activity are regulated via interactions with heterotrimeric Gβγ subunits, PIP 3 , and protein kinase A (PKA). Deletion analysis has further shown that domains C-terminal to its catalytic Dbl homology (DH) domain confer autoinhibition. Among these, the first dishevelled, Egl-10, and pleckstrin domain (DEP1) remains to be structurally characterized. DEP1 also harbors the primary PKA phosphorylation site, suggesting that an improved understanding of this region could substantially increase our knowledge of P-Rex1 signaling and open the door to new selective chemotherapeutics. Here we show that the DEP1 domain alone can autoinhibit activity in context of the DH/PH-DEP1 fragment of P-Rex1 and interacts with the DH/PH domains in solution. The 3.1 Å crystal structure of DEP1 features a domain swap, similar to that observed previously in the Dvl2 DEP domain, involving an exposed basic loop that contains the PKA site. Using purified proteins, we show that although DEP1 phosphorylation has no effect on the activity or solution conformation of the DH/PH-DEP1 fragment, it inhibits binding of the DEP1 domain to liposomes containing phosphatidic acid. Thus, we propose that PKA phosphorylation of the DEP1 domain hampers P-Rex1 binding to negatively charged membranes in cells, freeing the DEP1 domain to associate with and inhibit the DH/PH module.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Emergent actin flows explain distinct modes of gliding motility

During host infection, Toxoplasma gondii and related unicellular parasites move using gliding, which differs fundamentally from other known mechanisms of eukaryotic cell motility. Gliding is thought to be powered by a thin layer of flowing filamentous (F)-actin sandwiched between the plasma membrane and a myosin-covered inner membrane complex. How this surface actin layer drives the various gliding modes observed in experiments—helical, circular, twirling and patch, pendulum or rolling—is unclear. Here we suggest that F-actin flows arise through self-organization and develop a continuum model of emergent F-actin flow within the confines provided by Toxoplasma geometry. In the presence of F-actin turnover, our model predicts the emergence of a steady-state mode in which actin transport is largely directed rearward. Removing F-actin turnover leads to actin patches that recirculate up and down the cell, which we observe experimentally for drug-stabilized actin bundles in live Toxoplasma gondii parasites. These distinct self-organized actin states can account for observed gliding modes, illustrating how different forms of gliding motility can emerge as an intrinsic consequence of the self-organizing properties of F-actin flow in a confined geometry.

59 BASIC BIOLOGICAL SCIENCES↗

Periplasmic biomineralization for semi-artificial photosynthesis

Semiconductor-based biointerfaces are typically established either on the surface of the plasma membrane or within the cytoplasm. In Gram-negative bacteria, the periplasmic space, characterized by its confinement and the presence of numerous enzymes and peptidoglycans, offers additional opportunities for biomineralization, allowing for nongenetic modulation interfaces. We demonstrate semiconductor nanocluster precipitation containing single- and multiple-metal elements within the periplasm, as observed through various electron- and x-ray-based imaging techniques. The periplasmic semiconductors are metastable and display defect-dominant fluorescent properties. Unexpectedly, the defect-rich (i.e., the low-grade) semiconductor nanoclusters produced in situ can still increase adenosine triphosphate levels and malate production when coupled with photosensitization. We expand the sustainability levels of the biohybrid system to include reducing heavy metals at the primary level, building living bioreactors at the secondary level, and creating semi-artificial photosynthesis at the tertiary level. The biomineralization-enabled periplasmic biohybrids have the potential to serve as defect-tolerant platforms for diverse sustainable applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Localized phase contrast imaging at the Wendelstein 7-X stellarator

In its basic form, phase contrast imaging (PCI) provides line-integrated measurements of electron density fluctuations in plasmas. As turbulent fluctuations in magnetically confined plasmas have wave vectors almost perpendicular to the background magnetic field, the signals scattered by fluctuations from different parts of the PCI line-of-sight (LoS) are spatially separated in focal planes of the plasma. This allows localized PCI measurements by placing a mask in such a plane, to only permit signals from specific parts of the LoS to reach the PCI detectors. The present paper describes modeling and design of localization masks for the PCI system at the Wendelstein 7-X (W7-X) stellarator as well as the first results obtained using the masks in the recent long-pulse W7-X experimental campaign. During this project, we have extended the theory describing the mask response within the Fraunhofer diffraction model. As a novel development, we show from first principles that the mask response is determined by the fraction of power of the scattered beam spots that passes the mask. These insights have been used to select the W7-X mask design, consisting of a circular cutout, allowing the unscattered beam spot to pass the mask, with wedges covering a fixed angular range outside the central cutout. In the recent W7-X experimental campaign, the masks have verified the location of the main turbulence features observed by the PCI system and provided new information about the location of short-wavelength magnetohydrodynamic modes.

Physics↗

Measurement of atomic oxygen densities using TALIF on a dielectric barrier discharge: insights into the volume above a micro cavity plasma array

Dielectric barrier discharges, particularly micro cavity plasma arrays, offer significant potential for plasma-catalytic research due to their ability to ignite plasma in direct contact with a catalytic surface, enabling the observation of plasma-surface interactions. A key factor in their application is the generation of reactive species, such as atomic oxygen, within the cavities. These species can interact with both the surface (e.g. for activation or cleaning) and the gas being treated (e.g. for oxidation). Given the central role of oxygen atoms in plasma catalysis and their use as a model for more complex species, this work investigates the transport of these atoms out of the cavities. Two-photon absorption laser-induced fluorescence spectroscopy with picosecond laser excitation is performed in the volume above the cavities. The results are compared with a basic diffusion model. The reactor operates with a He/O 2 mixture at a flow rate of 1 slm and atmospheric pressure. Densities of up to 10 16 cm -3 are measured near the surface. Time-dependent measurements show that, at a distance of 350 µm from the surface, a density equilibrium is reached within less than 3 ms of reactor operation. Decay times due to ozone formation after the reactor is turned off are on a similar scale. Spatially resolved measurements show that the oxygen density decreases exponentially from the surface but remains detectable up to approximately 1 mm above the surface, indicating significant application potential. Variations in the O 2 admixture show a density maximum at 0.4%, confirming previous helium state enhanced actinometry measurements within the cavities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

CryoEM structures of the human CLC-2 voltage-gated chloride channel reveal a ball-and-chain gating mechanism

CLC-2 is a voltage-gated chloride channel that contributes to electrical excitability and ion homeostasis in many different tissues. Among the nine mammalian CLC homologs, CLC-2 is uniquely activated by hyperpolarization, rather than depolarization, of the plasma membrane. The molecular basis for the divergence in polarity of voltage gating among closely related homologs has been a long-standing mystery, in part because few CLC channel structures are available. Here, we report cryoEM structures of human CLC-2 at 2.46 – 2.76 Å, in the presence and absence of the selective inhibitor AK-42. AK-42 binds within the extracellular entryway of the Cl – -permeation pathway, occupying a pocket previously proposed through computational docking studies. In the apo structure, we observed two distinct conformations involving rotation of one of the cytoplasmic C-terminal domains (CTDs). In the absence of CTD rotation, an intracellular N-terminal 15-residue hairpin peptide nestles against the TM domain to physically occlude the Cl – -permeation pathway. This peptide is highly conserved among species variants of CLC-2 but is not present in other CLC homologs. Previous studies suggested that the N-terminal domain of CLC-2 influences channel properties via a “ball-and-chain” gating mechanism, but conflicting data cast doubt on such a mechanism, and thus the structure of the N-terminal domain and its interaction with the channel has been uncertain. Through electrophysiological studies of an N-terminal deletion mutant lacking the 15-residue hairpin peptide, we support a model in which the N-terminal hairpin of CLC-2 stabilizes a closed state of the channel by blocking the cytoplasmic Cl – -permeation pathway.

59 BASIC BIOLOGICAL SCIENCES↗

Database of pharmacokinetic time-series data and parameters for 144 environmental chemicals

Time courses of compound concentrations in plasma are used in chemical safety analysis to evaluate the relationship between external administered doses and internal tissue exposures. This type of experimental data is rarely available for the thousands of non-pharmaceutical chemicals to which people may potentially be unknowingly exposed but is necessary to properly assess the risk of such exposures. In vitro assays and in silico models are often used to craft an understanding of a chemical’s pharmacokinetics; however, the certainty of the quantitative application of these estimates for chemical safety evaluations cannot be determined without in vivo data for external validation. To address this need, we present a public database of chemical time-series concentration data from 567 studies in humans or test animals for 144 environmentally-relevant chemicals and their metabolites (187 analytes total). All major administration routes are incorporated, with concentrations measured in blood/plasma, tissues, and excreta. We also include calculated pharmacokinetic parameters for some studies, and a bibliography of additional source documents to support future extraction of time-series. In addition to pharmacokinetic model calibration and validation, these data may be used for analyses of diferential chemical distribution across chemicals, species, doses, or routes, and for meta-analyses on pharmacokinetic studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Functional characterization of a cellulose synthase, CtCESA1, from the marine red alga Calliarthron tuberculosum (Corallinales)

In land plants and algae, cellulose is important for strengthening cell walls and preventing breakage due to physical forces. Though our understanding of cellulose production by cellulose synthases (CESAs) has seen significant advances for several land plant and bacterial species, functional characterization of this fundamental protein is absent in red algae. Here we identify CESA gene candidates in the calcifying red alga Calliarthron tuberculosum using sequence similarity-based approaches, and elucidate their phylogenetic relationship with other CESAs from diverse taxa. One gene candidate, CtCESA1, was closely related to other putative red algal CESA genes. To test if CtCESA1 encoded a true cellulose synthase, CtCESA1 protein was expressed and purified from insect and yeast expression systems. CtCESA1 showed glucan synthase activity in glucose tracer assays. CtCESA1 activity was relatively low when compared with plant and bacterial CESA activity. In an in vitro assay, a predicted N-terminal starch-binding domain from CtCESA1 bound red algal floridean starch extracts, representing a unique domain in red algal CESAs not present in CESAs from other lineages. When the CtCESA1 gene was introduced into Arabidopsis thaliana cesa mutants, the red algal CtCESA1 partially rescued the growth defects of the primary cell wall cesa6 mutant, but not cesa3 or secondary cell wall cesa7 mutants. A fluorescently tagged CtCESA1 localized to the plasma membrane in the Arabidopsis cesa6 mutant background. This study presents functional evidence validating the sequence annotation of red algal CESAs. Furthermore, the relatively low activity of CtCESA1, partial complementation in Arabidopsis, and presence of unique protein domains suggest that there are probably functional differences between the algal and land plant CESAs.

59 BASIC BIOLOGICAL SCIENCES↗