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      Distinct functions of FASCILIN-LIKE ARABINOGALACTAN PROTEINS relate to domain structure

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          Abstract

          The role of glycoproteins as key cell surface molecules during development and stress is well established; yet, the relationship between their structural features and functional mechanisms is poorly defined. FASCICLIN-LIKE ARABINOGALACTAN PROTEINs (FLAs), which impact plant growth and development, are an excellent example of a glycoprotein family with a complex multidomain structure. FLAs combine globular fasciclin-like (FAS1) domains with regions that are intrinsically disordered and contain glycomotifs for directing the addition of O-linked arabinogalactan (AG) glycans. Additional posttranslational modifications on FLAs include N-linked glycans in the FAS1 domains, a cleaved signal peptide at the N terminus, and often a glycosylphosphatidylinositol (GPI) anchor signal sequence at the C terminus. The roles of glycosylation, the GPI anchor, and FAS1 domain functions in the polysaccharide-rich extracellular matrix of plants remain unclear, as do the relationships between them. In this study, we examined sequence–structure–function relationships of Arabidopsis ( Arabidopsis thaliana) FLA11, demonstrated to have roles in secondary cell wall (SCW) development, by introducing domain mutations and functional specialization through domain swaps with FLA3 and FLA12. We identified FAS1 domains as essential for FLA function, differentiating FLA11/FLA12, with roles in SCW development, from FLA3, specific to flowers and involved in pollen development. The GPI anchor and AG glycosylation co-regulate the cell surface location and release of FLAs into cell walls. The AG glycomotif sequence closest to the GPI anchor (AG2) is a major feature differentiating FLA11 from FLA12. The results of our study show that the multidomain structure of different FLAs influences their subcellular location and biological functions during plant development.

          Abstract

          Differences in subcellular location and biological functions of fasciclin-like arabinogalactan proteins rely on variations in their complex multidomain glycoprotein structure.

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          Most cited references48

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          Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

          The two most commonly used methods to analyze data from real-time, quantitative PCR experiments are absolute quantification and relative quantification. Absolute quantification determines the input copy number, usually by relating the PCR signal to a standard curve. Relative quantification relates the PCR signal of the target transcript in a treatment group to that of another sample such as an untreated control. The 2(-Delta Delta C(T)) method is a convenient way to analyze the relative changes in gene expression from real-time quantitative PCR experiments. The purpose of this report is to present the derivation, assumptions, and applications of the 2(-Delta Delta C(T)) method. In addition, we present the derivation and applications of two variations of the 2(-Delta Delta C(T)) method that may be useful in the analysis of real-time, quantitative PCR data. Copyright 2001 Elsevier Science (USA).
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            Highly accurate protein structure prediction with AlphaFold

            Proteins are essential to life, and understanding their structure can facilitate a mechanistic understanding of their function. Through an enormous experimental effort 1 – 4 , the structures of around 100,000 unique proteins have been determined 5 , but this represents a small fraction of the billions of known protein sequences 6 , 7 . Structural coverage is bottlenecked by the months to years of painstaking effort required to determine a single protein structure. Accurate computational approaches are needed to address this gap and to enable large-scale structural bioinformatics. Predicting the three-dimensional structure that a protein will adopt based solely on its amino acid sequence—the structure prediction component of the ‘protein folding problem’ 8 —has been an important open research problem for more than 50 years 9 . Despite recent progress 10 – 14 , existing methods fall far short of atomic accuracy, especially when no homologous structure is available. Here we provide the first computational method that can regularly predict protein structures with atomic accuracy even in cases in which no similar structure is known. We validated an entirely redesigned version of our neural network-based model, AlphaFold, in the challenging 14th Critical Assessment of protein Structure Prediction (CASP14) 15 , demonstrating accuracy competitive with experimental structures in a majority of cases and greatly outperforming other methods. Underpinning the latest version of AlphaFold is a novel machine learning approach that incorporates physical and biological knowledge about protein structure, leveraging multi-sequence alignments, into the design of the deep learning algorithm. AlphaFold predicts protein structures with an accuracy competitive with experimental structures in the majority of cases using a novel deep learning architecture.
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              Floral dip: a simplified method forAgrobacterium-mediated transformation ofArabidopsis thaliana

              The Agrobacterium vacuum infiltration method has made it possible to transform Arabidopsis thaliana without plant tissue culture or regeneration. In the present study, this method was evaluated and a substantially modified transformation method was developed. The labor-intensive vacuum infiltration process was eliminated in favor of simple dipping of developing floral tissues into a solution containing Agrobacterium tumefaciens, 5% sucrose and 500 microliters per litre of surfactant Silwet L-77. Sucrose and surfactant were critical to the success of the floral dip method. Plants inoculated when numerous immature floral buds and few siliques were present produced transformed progeny at the highest rate. Plant tissue culture media, the hormone benzylamino purine and pH adjustment were unnecessary, and Agrobacterium could be applied to plants at a range of cell densities. Repeated application of Agrobacterium improved transformation rates and overall yield of transformants approximately twofold. Covering plants for 1 day to retain humidity after inoculation also raised transformation rates twofold. Multiple ecotypes were transformable by this method. The modified method should facilitate high-throughput transformation of Arabidopsis for efforts such as T-DNA gene tagging, positional cloning, or attempts at targeted gene replacement.

                Author and article information

                Contributors
                Journal
                Plant Physiol
                Plant Physiol
                plphys
                Plant Physiology
                Oxford University Press (US )
                0032-0889
                1532-2548
                May 2023
                17 February 2023
                17 February 2023
                : 192
                : 1
                : 119-132
                Affiliations
                School of BioSciences, University of Melbourne , Parkville, VIC 3052, Australia
                La Trobe Institute for Sustainable Agriculture and Food, Department of Animal, Plant and Soil Science, La Trobe University , Bundoora, VIC 3086, Australia
                La Trobe Institute for Sustainable Agriculture and Food, Department of Animal, Plant and Soil Science, La Trobe University , Bundoora, VIC 3086, Australia
                La Trobe Institute for Sustainable Agriculture and Food, Department of Animal, Plant and Soil Science, La Trobe University , Bundoora, VIC 3086, Australia
                La Trobe Institute for Sustainable Agriculture and Food, Department of Animal, Plant and Soil Science, La Trobe University , Bundoora, VIC 3086, Australia
                CSIRO, Agriculture and Food, CSIRO Black Mountain Science and Innovation Park , Canberra, ACT 2601, Australia
                Department of Wood Science, University of British Columbia , Vancouver, BC V6T 1Z4, Canada
                La Trobe Institute for Sustainable Agriculture and Food, Department of Animal, Plant and Soil Science, La Trobe University , Bundoora, VIC 3086, Australia
                Sino-Australia Plant Cell Wall Research Centre, College of Forestry and Biotechnology, Zhejiang Agriculture and Forestry University , Lin’an, Hangzhou 311300, China
                La Trobe Institute for Sustainable Agriculture and Food, Department of Animal, Plant and Soil Science, La Trobe University , Bundoora, VIC 3086, Australia
                Sino-Australia Plant Cell Wall Research Centre, College of Forestry and Biotechnology, Zhejiang Agriculture and Forestry University , Lin’an, Hangzhou 311300, China
                Author notes
                Author for correspondence: k.johnson@ 123456latrobe.edu.au

                Y.M., K.L.J., and A.B. designed the research. T.S. and Y.M. designed FLA11 mutations; Y.M., K.L.J., C.P.M., and S.D.M. designed FLA domain swaps and functional domain concepts; Y.M. and A.M.M. constructed vectors and prepared transgenic plants; Y.M. and J.R. performed TEM imaging; Y.M. performed other experiments, analyzed data, and made the figures; Y.M., K.L.J., and A.B. wrote the manuscript with critical input from the other authors.

                The author responsible for distribution of materials integral to the findings presented in this article in accordance with the policy described in the Instructions for Authors ( https://academic.oup.com/plphys/pages/general-instructions) is: Kim L. Johnson ( k.johnson@ 123456latrobe.edu.au ).

                Conflict of interest statement. None declared.

                Author information
                https://orcid.org/0000-0002-0625-4242
                https://orcid.org/0000-0002-2298-7593
                https://orcid.org/0000-0003-4516-4650
                https://orcid.org/0000-0003-3594-5373
                https://orcid.org/0000-0002-0175-554X
                https://orcid.org/0000-0001-7483-8605
                https://orcid.org/0000-0001-6917-7742
                Article
                kiad097
                10.1093/plphys/kiad097
                10152678
                36797772
                1cb17d25-3a9a-42e4-a726-3815f46f73c0
                © The Author(s) 2023. Published by Oxford University Press on behalf of American Society of Plant Biologists.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 4 November 2022
                : 24 January 2023
                : 09 March 2023
                Page count
                Pages: 14
                Funding
                Funded by: University of Melbourne Research Scholarship, doi 10.13039/501100000987;
                Funded by: Albert Shimmins Fund;
                Funded by: Australia Research Council;
                Award ID: CE1101007
                Funded by: La Trobe Research Focus Area;
                Award ID: 2000004372
                Funded by: La Trobe University, doi 10.13039/501100001215;
                Funded by: Sino-Australia Plant Cell Wall Research Centre;
                Categories
                Research Article
                AcademicSubjects/SCI01270
                AcademicSubjects/SCI01280
                AcademicSubjects/SCI02286
                AcademicSubjects/SCI02287
                AcademicSubjects/SCI02288
                Plphys/16

                Plant science & Botany
                Plant science & Botany

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