Analysis of botanicals and botanical supplements by LC-MS/MS-based molecular networking: approaches for annotating plant metabolites and authentication
Ontology highlight
ABSTRACT:
INSTRUMENT(S): LTQ XL
ORGANISM(S): Actaea Racemosa (ncbitaxon:64040) Echinacea Purpurea (ncbitaxon:53751) Withania Somnifera (ncbitaxon:126910)
SUBMITTER: 
Matt Bertin
PROVIDER: MSV000088895 | MassIVE | Tue Feb 22 14:44:00 GMT 2022
REPOSITORIES: MassIVE
Similar Datasets
Project description:These data are LC-MS/MS files associated with the journal article (title above). Files represent botanical or supplement extracts and species and plant parts are designated in file titles. Additionally chromatography fractions are also identified as is a file for the standards used in the analysis (aloin A/B, echinacoside, berberine, withaferin A, 23-epi-26-deoxyactein). These files were used to create figures 2-6 and all supplementary networking figures.
2022-02-22 | MSV000088895 | GNPS
Project description:Prior to the advent of modern medicine, humans have used botanicals extensively for their therapeutic potential. With the majority of newly approved drugs having their origins in natural products, plants remain at the forefront of drug discovery. Continued research and discovery necessitate the use of high-throughput analytical methods to screen and identify bioactive components and potential therapeutic molecules from plants. Utilizing a pre-generated plant extract library, we subjected botanicals to LC-MS/MS-based molecular networking to determine their chemical composition and relatively quantify already known metabolites. The LC-MS/MS-based molecular networking approach was also used to authenticate the composition of dietary supplements against their corresponding plant specimens. The networking procedures provided concise visual representations of the chemical space and highly informative assessments of the botanicals. The procedures also proved to define the composition of the botanical supplements quickly and efficiently. This offered an innovative approach to metabolite profiling and authentication practices and additionally allowed for the identification of new, putatively unknown metabolites for future isolation and biological evaluation.
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Project description:In this study, we make used of mRNA-seq and its ability to reliably quantify isoforms, integrating this data with ribosome profiling and LC-MS/MS, to assign ribosome footprints and peptides at the isoform level. We leverage the principle that most cell types, and even tissues, predominantly express a single principal isoform to set isoform-level mRNA-seq quantifications as priors to guide and improve allocation of footprints or peptides to isoforms. Through tightly integrated mRNAseq, ribosome footprinting and/or LC-MS/MS proteomics we demonstrate that a principal isoform can be identified in over 80% of gene products in homogenous HEK293 cell culture and over 70% of proteins detected in complex human brain tissue. Defining isoforms in experiments with matched RNA-seq and translatomic/proteomic data increases the functional relevance of such datasets and will further broaden our understanding of multi-level control of gene expression. In this PRIDE submission you will find the raw files for the HEK293 cell proteomics. Files for the human brain proteomics can be found at PXD005445. We have also uploaded a zip file that contains the input files for our HEK293 cell analysis, and the isoform level output files – there is a separate folder within the zip files for these. The data used to create the manuscript figures is in the Rdata file. Code for assigning peptides and footprints to isoforms can be found on Github here: https://github.com/rkitchen/EMpire
2018-08-21 | PXD008693 | Pride
Project description:The ability to correlate the production of specialized metabolites to the genetic capacity of the organism that produces such molecules has become an invaluable tool in aiding the discovery of biotechnologically applicable molecules. Here, we accomplish this task by matching molecular families with gene cluster families, making these correlations to 60 microbes at one time instead of connecting one molecule to one organism at a time, such as how it is traditionally done. We can correlate these families through the use of nanospray desorption electrospray ionization MS/MS, an ambient pressure MS technique, in conjunction with MS/MS networking and peptidogenomics. We matched the molecular families of peptide natural products produced by 42 bacilli and 18 pseudomonads through the generation of amino acid sequence tags from MS/MS data of specific clusters found in the MS/MS network. These sequence tags were then linked to biosynthetic gene clusters in publicly accessible genomes, providing us with the ability to link particular molecules with the genes that produced them. As an example of its use, this approach was applied to two unsequenced Pseudoalteromonas species, leading to the discovery of the gene cluster for a molecular family, the bromoalterochromides, in the previously sequenced strain P. piscicida JCM 20779(T). The approach itself is not limited to 60 related strains, because spectral networking can be readily adopted to look at molecular family-gene cluster families of hundreds or more diverse organisms in one single MS/MS network.
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Project description:Heterocytous cyanobacteria are among the most prolific sources of bioactive secondary metabolites, including anabaenopeptins (APTs). A terrestrial filamentous Brasilonema sp. CT11 collected in Costa Rica bamboo forest as a black mat, was studied using a multidisciplinary approach: genome mining and HPLC-HRMS/MS coupled with bioinformatic analyses. Herein, we report the nearly complete genome consisting of 8.79 Mbp with a GC content of 42.4%. Moreover, we report on three novel tryptophan-containing APTs; anabaenopeptin 788 (1), anabaenopeptin 802 (2), and anabaenopeptin 816 (3). Furthermore, the structure of two homologues, i.e., anabaenopeptin 802 (2a) and anabaenopeptin 802 (2b), was determined by spectroscopic analysis (NMR and MS). Both compounds were shown to exert weak to moderate antiproliferative activity against HeLa cell lines. This study also provides the unique and diverse potential of biosynthetic gene clusters and an assessment of the predicted chemical space yet to be discovered from this genus.
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Project description:BACKGROUND:Herbicidin F has an undecose tricyclic furano-pyrano-pyran structure with post-decorations. It was detected from Streptomyces mobaraensis US-43 fermentation broth as a trace component by HPLC-MS analysis. As herbicidins exhibit herbicidal, antibacterial, antifungal and antiparasitic activities, we are attracted to explore more analogues for further development. RESULTS:The genome of S. mobaraensis US-43 was sequenced and a herbicidin biosynthetic gene cluster (hcd) was localized. The cluster contains structural genes, one transporter and three potential transcription regulatory genes. Overexpression of the three regulators respectively showed that only hcdR2 overexpression significantly improved the production of herbicidin F, and obviously increased the transcripts of 7 structural genes as well as the transporter gene. After performing homology searches using BLASTP in the GenBank database, 14 hcd-like clusters were found with a cluster-situated hcdR2 homologue. These HcdR2 orthologues showed overall structural similarity, especially in the C-terminal DNA binding domain. Based on bioinformatics analysis, a 21-bp consensus binding motif of HcdR2 was detected within 30 promoter regions in these genome-mined clusters. EMSA results verified that HcdR2 bound to the predicted consensus sequence. Additionally, we employed molecular networking to explore novel herbicidin analogues in hcdR2 overexpression strain. As a result, ten herbicidin analogues including six new compounds were identified based on MS/MS fragments. Herbicidin O was further purified and confirmed by 1H NMR spectrum. CONCLUSIONS:A herbicidin biosynthetic gene cluster (hcd) was identified in S. mobaraensis US-43. HcdR2, a member of LuxR family, was identified as the pathway-specific positive regulator, and the production of herbicidin F was dramatically increased by overexpression of hcdR2. Combined with molecular networking, ten herbicidin congeners including six novel herbicidin analogues were picked out from the secondary metabolites of hcdR2 overexpression strain. The orthologues of herbicidin F pathway-specific regulator HcdR2 were present in most of the genome-mined homologous biosynthetic gene clusters, which possessed at least one consensus binding motif with LuxR family characteristic. These results indicated that the combination of overexpression of hcdR2 orthologous regulator and molecular networking might be an effective way to exploit the "cryptic" herbicidin-related biosynthetic gene clusters for discovery of novel herbicidin analogues.
| S-EPMC6794829 | biostudies-literature
Project description:Man-made shallow fishponds in the Czech Republic have been facing high eutrophication since the 1950s. Anthropogenic eutrophication and feeding of fish have strongly affected the physicochemical properties of water and its aquatic community composition, leading to harmful algal bloom formation. In our current study, we characterized the phytoplankton community across three eutrophic ponds to assess the phytoplankton dynamics during the vegetation season. We microscopically identified and quantified 29 cyanobacterial taxa comprising non-toxigenic and toxigenic species. Further, a detailed cyanopeptides (CNPs) profiling was performed using molecular networking analysis of liquid chromatography-tandem mass spectrometry (LC-MS/MS) data coupled with a dereplication strategy. This MS networking approach, coupled with dereplication, on the online global natural product social networking (GNPS) web platform led us to putatively identify forty CNPs: fourteen anabaenopeptins, ten microcystins, five cyanopeptolins, six microginins, two cyanobactins, a dipeptide radiosumin, a cyclooctapeptide planktocyclin, and epidolastatin 12. We applied the binary logistic regression to estimate the CNPs producers by correlating the GNPS data with the species abundance. The usage of the GNPS web platform proved a valuable approach for the rapid and simultaneous detection of a large number of peptides and rapid risk assessments for harmful blooms.
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Project description:Turmeric, Curcuma longa L., is a type of medicinal plant characterized by its perennial nature and rhizomatous growth. It is a member of the Zingiberaceae family and is distributed across the world's tropical and subtropical climates, especially in South Asia. Its rhizomes have been highly valued for food supplements, spices, flavoring agents, and yellow dye in South Asia since ancient times. It exhibits a diverse array of therapeutic qualities that encompass its ability to combat diabetes, reduce inflammation, act as an antioxidant, exhibit anticancer properties, and promote anti-aging effects. In this study, organic extracts of C. longa rhizomes were subjected to HPLC separation followed by ESI-MS and low-energy tandem mass spectrometry analyses. The Global Natural Product Social Molecular Networking (GNPS) approach was utilized for the first time in this ethnobotanically important species to conduct an in-depth analysis of its metabolomes based on their fragments. To sum it up, a total of 30 metabolites including 16 diarylheptanoids, 1 diarylpentanoid, 3 bisabolocurcumin ethers, 4 sesquiterpenoids, 4 cinnamic acid derivatives, and 2 fatty acid derivatives were identified. Among the 16 diarylheptanoids identified in this study, 5 of them are reported for the first time in this species.
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Project description:Rmarkdown code, PDF, and Rdata file to recapitulate the paper's primary figures and machine learning model development.
| EGAD00001009764 | EGA
Project description:Temporal analysis of Irf4 and PU.1 genome binding during B cell activation and differentiation in vitro using antigen (NP-Ficoll) CD40L and IL-2/4/5 cytokines (see Molecular Systems Biology 7:495 for details of cellular system). The results provide insight in the target genes and binding specificity of IRF4 and PU.1 during coordination of different programs of B cell differentiation. Regrettably three of the FASTQ raw sequence files in our study were corrupted during storage. FASTQ data from our experimental and control groups are available for download via GEO SRA; however, two groups are missing select raw sequence files. These include one PU.1 Day 3 group file (Sample GSM1133499) and two of four input files used to generate a concatenated “super” input file (Sample GSM1133490); the raw data provided for input consists of the two input files recovered. Importantly, FASTA sequences for both of these datasets are available as supplementary data through GEO, and we can make available upon request (rsciamma@uchicago.edu) all files in our study in the ELAND-extended alignment format. Please note that GEO no longer supports this format.
2013-05-04 | GSE46607 | GEO