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      Inducing secondary metabolite production of Aspergillus sydowii through microbial co-culture with Bacillus subtilis

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          Abstract

          Background

          The co-culture strategy which mimics natural ecology by constructing an artificial microbial community is a useful tool to activate the biosynthetic gene clusters to generate new metabolites. However, the conventional method to study the co-culture is to isolate and purify compounds separated by HPLC, which is inefficient and time-consuming. Furthermore, the overall changes in the metabolite profile cannot be well characterized.

          Results

          A new approach which integrates computational programs, MS-DIAL, MS-FINDER and web-based tools including GNPS and MetaboAnalyst, was developed to analyze and identify the metabolites of the co-culture of Aspergillus sydowii and Bacillus subtilis. A total of 25 newly biosynthesized metabolites were detected only in co-culture. The structures of the newly synthesized metabolites were elucidated, four of which were identified as novel compounds by the new approach. The accuracy of the new approach was confirmed by purification and NMR data analysis of 7 newly biosynthesized metabolites. The bioassay of newly synthesized metabolites showed that four of the compounds exhibited different degrees of PTP1b inhibitory activity, and compound N2 had the strongest inhibition activity with an IC 50 value of 7.967 μM.

          Conclusions

          Co-culture led to global changes of the metabolite profile and is an effective way to induce the biosynthesis of novel natural products. The new approach in this study is one of the effective and relatively accurate methods to characterize the changes of metabolite profiles and to identify novel compounds in co-culture systems.

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          Most cited references43

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          Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking.

          The potential of the diverse chemistries present in natural products (NP) for biotechnology and medicine remains untapped because NP databases are not searchable with raw data and the NP community has no way to share data other than in published papers. Although mass spectrometry (MS) techniques are well-suited to high-throughput characterization of NP, there is a pressing need for an infrastructure to enable sharing and curation of data. We present Global Natural Products Social Molecular Networking (GNPS; http://gnps.ucsd.edu), an open-access knowledge base for community-wide organization and sharing of raw, processed or identified tandem mass (MS/MS) spectrometry data. In GNPS, crowdsourced curation of freely available community-wide reference MS libraries will underpin improved annotations. Data-driven social-networking should facilitate identification of spectra and foster collaborations. We also introduce the concept of 'living data' through continuous reanalysis of deposited data.
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            Using MetaboAnalyst 3.0 for Comprehensive Metabolomics Data Analysis.

            MetaboAnalyst (http://www.metaboanalyst.ca) is a comprehensive Web application for metabolomic data analysis and interpretation. MetaboAnalyst handles most of the common metabolomic data types from most kinds of metabolomics platforms (MS and NMR) for most kinds of metabolomics experiments (targeted, untargeted, quantitative). In addition to providing a variety of data processing and normalization procedures, MetaboAnalyst also supports a number of data analysis and data visualization tasks using a range of univariate, multivariate methods such as PCA (principal component analysis), PLS-DA (partial least squares discriminant analysis), heatmap clustering and machine learning methods. MetaboAnalyst also offers a variety of tools for metabolomic data interpretation including MSEA (metabolite set enrichment analysis), MetPA (metabolite pathway analysis), and biomarker selection via ROC (receiver operating characteristic) curve analysis, as well as time series and power analysis. This unit provides an overview of the main functional modules and the general workflow of the latest version of MetaboAnalyst (MetaboAnalyst 3.0), followed by eight detailed protocols. © 2016 by John Wiley & Sons, Inc.
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              Biological network exploration with cytoscape 3.

              Cytoscape is one of the most popular open-source software tools for the visual exploration of biomedical networks composed of protein, gene, and other types of interactions. It offers researchers a versatile and interactive visualization interface for exploring complex biological interconnections supported by diverse annotation and experimental data, thereby facilitating research tasks such as predicting gene function and constructing pathways. Cytoscape provides core functionality to load, visualize, search, filter, and save networks, and hundreds of Apps extend this functionality to address specific research needs. The latest generation of Cytoscape (version 3.0 and later) has substantial improvements in function, user interface, and performance relative to previous versions. This protocol aims to jump-start new users with specific protocols for basic Cytoscape functions, such as installing Cytoscape and Cytoscape Apps, loading data, visualizing and navigating the networks, visualizing network associated data (attributes), and identifying clusters. It also highlights new features that benefit experienced users. Curr. Protoc. Bioinform. 47:8.13.1-8.13.24. © 2014 by John Wiley & Sons, Inc. Copyright © 2014 John Wiley & Sons, Inc.
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                Author and article information

                Contributors
                lium@im.ac.cn
                yshdong@dlut.edu.cn
                Journal
                Microb Cell Fact
                Microb Cell Fact
                Microbial Cell Factories
                BioMed Central (London )
                1475-2859
                12 February 2021
                12 February 2021
                2021
                : 20
                : 42
                Affiliations
                [1 ]GRID grid.30055.33, ISNI 0000 0000 9247 7930, School of Bioengineering, , Dalian University of Technology, ; DalianLiaoning, 116024 China
                [2 ]New Drug Research and Development Center, North China Pharmaceutical Group Corporation and National Microbial Medicine Engineering and Research Center, Shijiazhuang, 050015 Hebei China
                [3 ]GRID grid.9227.e, ISNI 0000000119573309, CAS Key Laboratory of Microbial Physiological and Metabolic Engineering, Institute of Microbiology, , Chinese Academy of Sciences, ; Beijing, 100101 China
                [4 ]GRID grid.410726.6, ISNI 0000 0004 1797 8419, University of Chinese Academy of Sciences, ; Beijing, 101408 China
                [5 ]Shandong New Time Pharmaceutical Co., Ltd, Shandong, 255000 China
                Author information
                http://orcid.org/0000-0001-5010-6426
                Article
                1527
                10.1186/s12934-021-01527-0
                7881642
                33579268
                7c1f0cd0-bcdf-4f1a-9d0e-e0af8c2f6c45
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 6 December 2020
                : 22 January 2021
                Funding
                Funded by: National Natural Science Foundation of China
                Award ID: 31670052
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100005047, Natural Science Foundation of Liaoning Province;
                Award ID: 2019-ZD-0143
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2021

                Biotechnology
                aspergillus sydowii,bacillus subtilis,co-culture,natural products
                Biotechnology
                aspergillus sydowii, bacillus subtilis, co-culture, natural products

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