Phosphoproteome analysis reveals an extensive phosphorylation of proteins associated with bast fiber growth in ramie.
TL;DR: In this article, the role of phosphorylation modification in the growth of Ramie fibers is investigated, and the authors found that differentially phosphorylated KNOX protein whole_GLEAN_10029667 dramatically repressed fiber formation in Arabidopsis.
Abstract: BACKGROUND Phosphorylation modification, one of the most common post-translational modifications of proteins, widely participates in the regulation of plant growth and development. Fibers extracted from the stem bark of ramie are important natural textile fibers; however, the role of phosphorylation modification in the growth of ramie fibers is largely unknown. RESULTS Here, we report a phosphoproteome analysis for the barks from the top and middle section of ramie stems, in which the fiber grows at different stages. A total of 10,320 phosphorylation sites from 9,170 unique phosphopeptides that were assigned to 3,506 proteins was identified, and 458 differentially phosphorylated sites from 323 proteins were detected in the fiber developmental barks. Twelve differentially phosphorylated proteins were the homologs of Arabidopsis fiber growth-related proteins. We further focused on the function of the differentially phosphorylated KNOX protein whole_GLEAN_10029667, and found that this protein dramatically repressed the fiber formation in Arabidopsis. Additionally, using a yeast two-hybridization assay, we identified a kinase and a phosphatase that interact with whole_GLEAN_10029667, indicating that they potentially target this KNOX protein to regulate its phosphorylation level. CONCLUSION The finding of this study provided insights into the involvement of phosphorylation modification in ramie fiber growth, and our functional characterization of whole_GLEAN_10029667 provide the first evidence to indicate the involvement of phosphorylation modification in the regulation of KNOX protein function in plants.
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TL;DR: Wang et al. as mentioned in this paper performed a proteomic analysis of the bark from the top and middle parts of the stem, where fiber growth is at different stages, and identified 6971 non-redundant proteins from bast bark.
Abstract: BACKGROUND Ramie is an important fiber-producing crop in China, and its fibers are widely used as textile materials. Fibers contain specialized secondary cellular walls that are mainly composed of cellulose, hemicelluloses, and lignin. Understanding the mechanism underlying the secondary wall biosynthesis of fibers will benefit the improvement of fiber yield and quality in ramie. RESULTS Here, we performed a proteomic analysis of the bark from the top and middle parts of the stem, where fiber growth is at different stages. We identified 6971 non-redundant proteins from bast bark. Proteomic comparison revealed 983 proteins with differential expression between the two bark types. Of these 983 proteins, 46 were identified as the homolog of known secondary wall biosynthetic proteins of Arabidopsis, indicating that they were potentially associated with fiber growth. Then, we proposed a molecular model for the secondary wall biosynthesis of ramie fiber. Furthermore, interaction analysis of 46 candidate proteins revealed two interacting networks that consisted of eight cellulose biosynthetic enzymes and seven lignin biosynthetic proteins, respectively. CONCLUSION This study sheds light on the proteomic basis underlying bast fiber growth in ramie, and the identification of many candidates associated with fiber growth provides important basis for understanding the fiber growth in this crop.
4 citations
01 Jan 2023
TL;DR: In this article , a review of the materials, workflows, and applications of IMAC for phosphoproteomic profiling is presented, including a brief discussion on their advantages, current challenges, and trends in the future development.
Abstract: The last ten years have witnessed the increasingly notable advances in immobilized metal ion chromatography (IMAC) for phosphoproteomic profiling. Protein phosphorylation is an important post-translational modification (PTM) that participates in multiple cellular processes. Phosphoproteomics provides powerful analysis and unique insights for the study of phosphorylation-related cellular processes and disease mechanisms. IMAC enrichment strategy could capture phosphopeptides with chemical interaction between the phosphoamino acids and the immobilized metal cations. Currently, IMAC materials and workflows have matured and are applied in capturing phosphopeptides at substoichiometric levels. The design of IMAC enrichment materials and matching workflows are particularly vital in phosphoproteomic profiling. This review mainly focuses on overviewing present advances in the materials, workflows, and applications of immobilized metal ion chromatography for phosphoproteomic profiling, including a brief discussion on their advantages, current challenges, and trends in the future development.
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TL;DR: The 2-Delta Delta C(T) method as mentioned in this paper was proposed to analyze the relative changes in gene expression from real-time quantitative PCR experiments, and it has been shown to be useful in the analysis of realtime, quantitative PCR data.
139,407 citations
TL;DR: The newest addition in MEGA5 is a collection of maximum likelihood (ML) analyses for inferring evolutionary trees, selecting best-fit substitution models, inferring ancestral states and sequences, and estimating evolutionary rates site-by-site.
Abstract: Comparative analysis of molecular sequence data is essential for reconstructing the evolutionary histories of species and inferring the nature and extent of selective forces shaping the evolution of genes and species. Here, we announce the release of Molecular Evolutionary Genetics Analysis version 5 (MEGA5), which is a user-friendly software for mining online databases, building sequence alignments and phylogenetic trees, and using methods of evolutionary bioinformatics in basic biology, biomedicine, and evolution. The newest addition in MEGA5 is a collection of maximum likelihood (ML) analyses for inferring evolutionary trees, selecting best-fit substitution models (nucleotide or amino acid), inferring ancestral states and sequences (along with probabilities), and estimating evolutionary rates site-by-site. In computer simulation analyses, ML tree inference algorithms in MEGA5 compared favorably with other software packages in terms of computational efficiency and the accuracy of the estimates of phylogenetic trees, substitution parameters, and rate variation among sites. The MEGA user interface has now been enhanced to be activity driven to make it easier for the use of both beginners and experienced scientists. This version of MEGA is intended for the Windows platform, and it has been configured for effective use on Mac OS X and Linux desktops. It is available free of charge from http://www.megasoftware.net.
39,110 citations
TL;DR: ClUSTAL X is a new windows interface for the widely-used progressive multiple sequence alignment program CLUSTAL W, providing an integrated system for performing multiple sequence and profile alignments and analysing the results.
Abstract: CLUSTAL X is a new windows interface for the widely-used progressive multiple sequence alignment program CLUSTAL W. The new system is easy to use, providing an integrated system for performing multiple sequence and profile alignments and analysing the results. CLUSTAL X displays the sequence alignment in a window on the screen. A versatile sequence colouring scheme allows the user to highlight conserved features in the alignment. Pull-down menus provide all the options required for traditional multiple sequence and profile alignment. New features include: the ability to cut-and-paste sequences to change the order of the alignment, selection of a subset of the sequences to be realigned, and selection of a sub-range of the alignment to be realigned and inserted back into the original alignment. Alignment quality analysis can be performed and low-scoring segments or exceptional residues can be highlighted. Quality analysis and realignment of selected residue ranges provide the user with a powerful tool to improve and refine difficult alignments and to trap errors in input sequences. CLUSTAL X has been compiled on SUN Solaris, IRIX5.3 on Silicon Graphics, Digital UNIX on DECstations, Microsoft Windows (32 bit) for PCs, Linux ELF for x86 PCs, and Macintosh PowerMac.
38,522 citations
TL;DR: H hierarchical and self-consistent orthology annotations are introduced for all interacting proteins, grouping the proteins into families at various levels of phylogenetic resolution in the STRING database.
Abstract: The many functional partnerships and interactions that occur between proteins are at the core of cellular processing and their systematic characterization helps to provide context in molecular systems biology. However, known and predicted interactions are scattered over multiple resources, and the available data exhibit notable differences in terms of quality and completeness. The STRING database (http://string-db.org) aims to provide a critical assessment and integration of protein-protein interactions, including direct (physical) as well as indirect (functional) associations. The new version 10.0 of STRING covers more than 2000 organisms, which has necessitated novel, scalable algorithms for transferring interaction information between organisms. For this purpose, we have introduced hierarchical and self-consistent orthology annotations for all interacting proteins, grouping the proteins into families at various levels of phylogenetic resolution. Further improvements in version 10.0 include a completely redesigned prediction pipeline for inferring protein-protein associations from co-expression data, an API interface for the R computing environment and improved statistical analysis for enrichment tests in user-provided networks.
8,224 citations
TL;DR: WoLF PSORT converts protein amino acid sequences into numerical localization features; based on sorting signals, amino acid composition and functional motifs such as DNA-binding motifs, which allows a user to understand the evidence (or lack thereof) behind the predictions made for particular proteins.
Abstract: WoLF PSORT is an extension of the PSORT II program for protein subcellular location prediction. WoLF PSORT converts protein amino acid sequences into numerical localization features; based on sorting signals, amino acid composition and functional motifs such as DNA-binding motifs. After conversion, a simple k-nearest neighbor classifier is used for prediction. Using html, the evidence for each prediction is shown in two ways: (i) a list of proteins of known localization with the most similar localization features to the query, and (ii) tables with detailed information about individual localization features. For convenience, sequence alignments of the query to similar proteins and links to UniProt and Gene Ontology are provided. Taken together, this information allows a user to understand the evidence (or lack thereof) behind the predictions made for particular proteins. WoLF PSORT is available at wolfpsort.org
2,878 citations