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Venn diagrams serve as invaluable tools for visualizing set relationships due to their ease of interpretation. Widely applied across diverse disciplines such as metabolomics, genomics, transcriptomics, and proteomics, their utility is undeniable. However, the operational complexity has been compounded by the absence of standardized data formats and the need to switch between various platforms for generating different Venn diagrams. To address these challenges, we introduce the EVenn platform, a versatile tool offering a unified interface for efficient data exploration and visualization of diverse Venn diagrams. EVenn (http://www.ehbio.com/test/venn) streamlines the data upload process with a standardized format, enhancing the capabilities for multimodule analysis. This comprehensive protocol outlines various applications of EVenn, featuring representative results of multiple Venn diagrams, data uploads in the centralized data center, and step‐by‐step case demonstrations. Through these functionalities, EVenn emerges as a valuable and user‐friendly tool for the in‐depth exploration of multiomics data. Highlights: Comprehensive Venn functionality: EVenn introduces a unified platform with diverse Venn diagram tools, from interactive diagrams to network representations, catering to the intricate needs of multiomics data analysis across metabolomics, genomics, transcriptomics, and proteomics.Efficient data exploration: EVenn's data center streamlines exploration by supporting a standardized data format, allowing researchers to effortlessly upload and analyze data. The manuscript demonstrates its practical utility through representative results and detailed case demonstrations.User‐friendly interface: With a user‐friendly interface, EVenn simplifies the generation of various Venn diagrams, Euler diagrams, UpSet plots, and more. This protocol establishes EVenn as a valuable resource for researchers seeking a cohesive and accessible tool for multiomics data interpretation. [ABSTRACT FROM AUTHOR]

Improved signal identification for biological small molecules (BSMs) in a mixture was demonstrated by using multidimensional NMR on samples from 13C-enriched Rhododendron japonicum (59.5 atom%) cultivated in air containing 13C-labeled carbon dioxide for 14 weeks. The resonance assignment of 386 carbon atoms and 380 hydrogen atoms in the mixture was achieved. 42 BSMs, including eight that were unlisted in the spectral databases, were identified. Comparisons between the experimental values and the 13C chemical shift values calculated by density functional theory supported the identifications of unlisted BSMs. Tracing the 13C/12C ratio by multidimensional NMR spectra revealed faster and slower turnover ratios of BSMs involved in central metabolism and those categorized as secondary metabolites, respectively. The identification of BSMs and subsequent flow analysis provided insight into the metabolic systems of the plant. [ABSTRACT FROM AUTHOR]

Improved signal identification for biological small molecules (BSMs) in a mixture was demonstrated by using multidimensional NMR on samples from 13C-enriched Rhododendron japonicum (59.5 atom%) cultivated in air containing 13C-labeled carbon dioxide for 14 weeks. The resonance assignment of 386 carbon atoms and 380 hydrogen atoms in the mixture was achieved. 42 BSMs, including eight that were unlisted in the spectral databases, were identified. Comparisons between the experimental values and the 13C chemical shift values calculated by density functional theory supported the identifications of unlisted BSMs. Tracing the 13C/12C ratio by multidimensional NMR spectra revealed faster and slower turnover ratios of BSMs involved in central metabolism and those categorized as secondary metabolites, respectively. The identification of BSMs and subsequent flow analysis provided insight into the metabolic systems of the plant. [ABSTRACT FROM AUTHOR]

Bacteria-derived enzymes that can modify specific lignin substructures are potential targets to engineer plants for better biomass processability. The Gram-negative bacterium Sphingobium sp. SYK-6 possesses a Cα-dehydrogenase (LigD) enzyme that has been shown to oxidize the α-hydroxy functionalities in β-O-4-linked dimers into α-keto analogues that are more chemically labile. Here, we show that recombinant LigD can oxidize an even wider range of β-O-4-linked dimers and oligomers, including the genuine dilignols, guaiacylglycerol-β-coniferyl alcohol ether and syringylglycerol-β-sinapyl alcohol ether. We explored the possibility of using LigD for biosynthetically engineering lignin by expressing the codon-optimized ligD gene in Arabidopsis thaliana. The ligD cDNA, with or without a signal peptide for apoplast targeting, has been successfully expressed, and LigD activity could be detected in the extracts of the transgenic plants. UPLC- MS/ MS-based metabolite profiling indicated that levels of oxidized guaiacyl (G) β-O-4-coupled dilignols and analogues were significantly elevated in the LigD transgenic plants regardless of the signal peptide attachment to LigD. In parallel, 2D NMR analysis revealed a 2.1- to 2.8-fold increased level of G-type α-keto-β-O-4 linkages in cellulolytic enzyme lignins isolated from the stem cell walls of the LigD transgenic plants, indicating that the transformation was capable of altering lignin structure in the desired manner. [ABSTRACT FROM AUTHOR]