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      Exploring the diversity, bioactivity of endophytes, and metabolome in Synsepalum dulcificum

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          Abstract

          Synsepalum dulcificum exhibits high edible and medicinal value; however, there have been no reports on the exploration of its endophyte resources. Here, we conducted analyses encompassing plant metabolomics, microbial diversity, and the biological activities of endophytic metabolites in S. dulcificum. High-throughput sequencing identified 4,913 endophytic fungal amplicon sequence variants (ASVs) and 1,703 endophytic bacterial ASVs from the roots, stems, leaves, flowers, and fruits of S. dulcificum. Fungi were classified into 5 phyla, 24 classes, 75 orders, 170 families, and 313 genera, while bacteria belonged to 21 phyla, 47 classes, 93 orders, 145 families, and 232 genera. Furthermore, there were significant differences in the composition and content of metabolites in different tissues of S. dulcificum. Spearman’s correlation analysis of the differential metabolites and endophytes revealed that the community composition of the endophytes correlated with plant-rich metabolites. The internal transcribed spacer sequences of 105 isolates were determined, and phylogenetic analyses revealed that these fungi were distributed into three phyla (Ascomycota, Basidiomycota, and Mucoromycota) and 20 genera. Moreover, 16S rDNA sequencing of 46 bacteria revealed they were distributed in 16 genera in three phyla: Actinobacteria, Proteobacteria, and Firmicutes. The antimicrobial activities (filter paper method) and antioxidant activity (DPPH and ABTS assays) of crude extracts obtained from 68 fungal and 20 bacterial strains cultured in different media were evaluated. Additionally, the α-glucosidase inhibitory activity of the fungal extracts was examined. The results showed that 88.6% of the strains exhibited antimicrobial activity, 55.7% exhibited antioxidant activity, and 85% of the fungi exhibited α-glucosidase inhibitory activity. The research suggested that the endophytes of S. dulcificum are highly diverse and have the potential to produce bioactive metabolites, providing abundant species resources for developing antibiotics, antioxidants and hypoglycemic drugs.

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          Introducing EzTaxon-e: a prokaryotic 16S rRNA gene sequence database with phylotypes that represent uncultured species.

          Despite recent advances in commercially optimized identification systems, bacterial identification remains a challenging task in many routine microbiological laboratories, especially in situations where taxonomically novel isolates are involved. The 16S rRNA gene has been used extensively for this task when coupled with a well-curated database, such as EzTaxon, containing sequences of type strains of prokaryotic species with validly published names. Although the EzTaxon database has been widely used for routine identification of prokaryotic isolates, sequences from uncultured prokaryotes have not been considered. Here, the next generation database, named EzTaxon-e, is formally introduced. This new database covers not only species within the formal nomenclatural system but also phylotypes that may represent species in nature. In addition to an identification function based on Basic Local Alignment Search Tool (blast) searches and pairwise global sequence alignments, a new objective method of assessing the degree of completeness in sequencing is proposed. All sequences that are held in the EzTaxon-e database have been subjected to phylogenetic analysis and this has resulted in a complete hierarchical classification system. It is concluded that the EzTaxon-e database provides a useful taxonomic backbone for the identification of cultured and uncultured prokaryotes and offers a valuable means of communication among microbiologists who routinely encounter taxonomically novel isolates. The database and its analytical functions can be found at http://eztaxon-e.ezbiocloud.net/.
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            XCMS: processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification.

            Metabolite profiling in biomarker discovery, enzyme substrate assignment, drug activity/specificity determination, and basic metabolic research requires new data preprocessing approaches to correlate specific metabolites to their biological origin. Here we introduce an LC/MS-based data analysis approach, XCMS, which incorporates novel nonlinear retention time alignment, matched filtration, peak detection, and peak matching. Without using internal standards, the method dynamically identifies hundreds of endogenous metabolites for use as standards, calculating a nonlinear retention time correction profile for each sample. Following retention time correction, the relative metabolite ion intensities are directly compared to identify changes in specific endogenous metabolites, such as potential biomarkers. The software is demonstrated using data sets from a previously reported enzyme knockout study and a large-scale study of plasma samples. XCMS is freely available under an open-source license at http://metlin.scripps.edu/download/.
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              Plant–microbiome interactions: from community assembly to plant health

              Healthy plants host diverse but taxonomically structured communities of microorganisms, the plant microbiota, that colonize every accessible plant tissue. Plant-associated microbiomes confer fitness advantages to the plant host, including growth promotion, nutrient uptake, stress tolerance and resistance to pathogens. In this Review, we explore how plant microbiome research has unravelled the complex network of genetic, biochemical, physical and metabolic interactions among the plant, the associated microbial communities and the environment. We also discuss how those interactions shape the assembly of plant-associated microbiomes and modulate their beneficial traits, such as nutrient acquisition and plant health, in addition to highlighting knowledge gaps and future directions.
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                Author and article information

                Contributors
                Role: Role: Role: Role:
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                URI : http://loop.frontiersin.org/people/413209/overviewRole: Role: Role:
                URI : http://loop.frontiersin.org/people/2283312/overviewRole: Role: Role:
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                27 February 2024
                2024
                : 15
                : 1258208
                Affiliations
                [1] 1Key Laboratory for Southwest Microbial Diversity of the Ministry of Education, Yunnan Institute of Microbiology, School of Life Sciences, Yunnan University , Kunming, China
                [2] 2Department of Gardening and Horticulture, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Mengla County , Yunnan, China
                Author notes

                Edited by: Luke Moe, University of Kentucky, United States

                Reviewed by: Fengyu Du, Qingdao Agricultural University, China

                Samantha Chandranath Karunarathna, Qujing Normal University, China

                Walaa K. Mousa, Mansoura University, Egypt

                *Correspondence: Shaohua Wu, shwu123@ 123456126.com
                Article
                10.3389/fmicb.2024.1258208
                10929569
                38476934
                14151943-febe-48f8-80b9-a3931df683b4
                Copyright © 2024 Liu, Hou, Zheng, Ma, Wen, Shao and Wu.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 13 July 2023
                : 12 February 2024
                Page count
                Figures: 9, Tables: 2, Equations: 7, References: 50, Pages: 17, Words: 11741
                Funding
                The author(s) declare financial support was received for the research, authorship, and/or publication of the article. This research was financially supported by the National Natural Science Foundation of China (grant No. 32260110) and Yunnan Fundamental Research Projects (grant Nos. 202201BF070001-003 and 202001BB050029).
                Categories
                Microbiology
                Original Research
                Custom metadata
                Microbe and Virus Interactions with Plants

                Microbiology & Virology
                synsepalum dulcificum,microbiome,metabolomics,endophytes,diversity,biological activities

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